Lead Data Engineer Manchester Hybrid Circa £85K An established organisation is looking for a hands-on Lead Data Engineer to take ownership of its existing data estate and lead the development of a modern, scalable data platform. This is an excellent opportunity to build a platform supporting Business Intelligence, Data Science and Applied AI. You'll introduce modern batch and real-time data-processing capabilities, automate inefficient processes and make trusted data more accessible across the organisation. Alongside remaining technically hands-on, you'll manage and develop a small team of Data Engineers. Key responsibilities Own the reliability, security and ongoing development of the data platform. Modernise the existing SQL Server, SSIS/SSDT and Power BI environment. Develop scalable batch and real-time data-processing solutions. Lead the design of a Customer Data Platform. Build and evolve a lakehouse architecture using AWS technologies. Create governed semantic models, consistent metrics and clear data definitions. Enable secure, self-service data analysis using modern AI tooling. Automate manual, repetitive or fragile data processes. Support BI, Data Science, Machine Learning and Applied AI teams. Take ownership of data governance, security, monitoring and platform costs. Line-manage, develop and help grow the Data Engineering team. Work closely with technical, operational and senior business stakeholders. Skills and experience We're looking for an experienced Data Engineer who has built and operated complete data platforms rather than solely delivering individual components. You'll need experience across: Batch data processing, ELT and orchestration. Modern streaming technologies such as Flink or comparable platforms. AWS data services, including S3, Lambda, Glue, Athena, Kinesis and RDS. Infrastructure as code using Terraform. CI/CD and automated testing. Lakehouse architecture and open table formats such as Iceberg. Medallion architecture and dimensional data modelling. Strong SQL and Python. SQL Server, SSIS/SSDT and Power BI. Semantic layers, common metrics and data glossaries. Data governance, lineage, retention, classification and auditability. Managing and developing a small technical team. You should also be comfortable using advanced AI coding assistants, such as Claude Code or equivalent tools, to improve engineering productivity while maintaining high standards of quality, governance and security. Desirable experience Regulated environment. PySpark for large-scale data transformations. Migrating legacy data estates to lakehouse or metadata-driven architectures. Customer Data Platforms or event-driven systems. Data-quality tools such as dbt tests or Great Expectations. MCP servers or governed natural-language data interfaces. Financial crime, fraud or regulatory-reporting data. Power BI administration and semantic modelling. The opportunity This is a genuinely influential role where you'll own the data platform end to end and help shape how data and AI are used across the organisation. You'll have the scope to introduce modern technologies, remove unnecessary manual work and build a platform capable of supporting future products, analytics and business decision-making. Salary: Circa £85K Location: Manchester Working pattern: Hybrid Lead Data Engineer - Manchester
Oct 10, 2026
Full time
Lead Data Engineer Manchester Hybrid Circa £85K An established organisation is looking for a hands-on Lead Data Engineer to take ownership of its existing data estate and lead the development of a modern, scalable data platform. This is an excellent opportunity to build a platform supporting Business Intelligence, Data Science and Applied AI. You'll introduce modern batch and real-time data-processing capabilities, automate inefficient processes and make trusted data more accessible across the organisation. Alongside remaining technically hands-on, you'll manage and develop a small team of Data Engineers. Key responsibilities Own the reliability, security and ongoing development of the data platform. Modernise the existing SQL Server, SSIS/SSDT and Power BI environment. Develop scalable batch and real-time data-processing solutions. Lead the design of a Customer Data Platform. Build and evolve a lakehouse architecture using AWS technologies. Create governed semantic models, consistent metrics and clear data definitions. Enable secure, self-service data analysis using modern AI tooling. Automate manual, repetitive or fragile data processes. Support BI, Data Science, Machine Learning and Applied AI teams. Take ownership of data governance, security, monitoring and platform costs. Line-manage, develop and help grow the Data Engineering team. Work closely with technical, operational and senior business stakeholders. Skills and experience We're looking for an experienced Data Engineer who has built and operated complete data platforms rather than solely delivering individual components. You'll need experience across: Batch data processing, ELT and orchestration. Modern streaming technologies such as Flink or comparable platforms. AWS data services, including S3, Lambda, Glue, Athena, Kinesis and RDS. Infrastructure as code using Terraform. CI/CD and automated testing. Lakehouse architecture and open table formats such as Iceberg. Medallion architecture and dimensional data modelling. Strong SQL and Python. SQL Server, SSIS/SSDT and Power BI. Semantic layers, common metrics and data glossaries. Data governance, lineage, retention, classification and auditability. Managing and developing a small technical team. You should also be comfortable using advanced AI coding assistants, such as Claude Code or equivalent tools, to improve engineering productivity while maintaining high standards of quality, governance and security. Desirable experience Regulated environment. PySpark for large-scale data transformations. Migrating legacy data estates to lakehouse or metadata-driven architectures. Customer Data Platforms or event-driven systems. Data-quality tools such as dbt tests or Great Expectations. MCP servers or governed natural-language data interfaces. Financial crime, fraud or regulatory-reporting data. Power BI administration and semantic modelling. The opportunity This is a genuinely influential role where you'll own the data platform end to end and help shape how data and AI are used across the organisation. You'll have the scope to introduce modern technologies, remove unnecessary manual work and build a platform capable of supporting future products, analytics and business decision-making. Salary: Circa £85K Location: Manchester Working pattern: Hybrid Lead Data Engineer - Manchester
Lead Data Engineer (AI & Data Platforms) Must Be DV Clearable 5 Days Onsite Hands-on technical leadership building data and AI systems that actually work We're looking for a Lead Data Engineer to join a growing enterprise data and AI capability, playing a critical role in designing, building, and operating production-grade data platforms and AI-enabled solutions. This is not a line-management role . Instead, it is a senior, hands-on technical leadership position for someone with deep data engineering experience who leads through delivery, technical judgement, and engineering excellence rather than hierarchy. You will work across complex environments spanning legacy platforms, modern cloud services, advanced analytics, machine learning, and emerging AI technologies. The challenge isn't greenfield experimentation; it's building robust production systems, operationalising AI capabilities, improving what exists, and helping teams use data and AI safely, effectively, and at scale. We're particularly interested in engineers who have helped organisations establish the foundations for AI-led development, including data platforms, ML pipelines, governance frameworks, deployment processes, and production support models. What You'll Be Doing You'll act as a senior technical anchor for both data engineering and AI-enablement initiatives, contributing directly while guiding others through example. You will: Design, build, and enhance enterprise-scale data platforms, pipelines, and services Lead complex data engineering work end-to-end, from problem definition and exploration through build, testing, deployment, and operational support Build and maintain cloud-native data platforms that support analytics, machine learning, and AI workloads Develop robust data pipelines supporting both traditional analytics and AI/ML use cases Work directly with technical and non-technical stakeholders to translate operational problems into scalable data and AI solutions Design data models, integration patterns, and storage structures that support long-term maintainability and reusability Help establish engineering frameworks for AI-led development, including environments, CI/CD processes, testing strategies, governance controls, and deployment standards Support the operationalisation of machine learning and AI solutions into production environments Improve data sharing, onboarding of new data sources, and interoperability across teams and systems Evaluate and introduce new tools, frameworks, and technologies where they deliver genuine value Build robust, production-grade solutions rather than proofs of concept Treat metadata, lineage, observability, governance, data quality, and security as first-class engineering concerns Diagnose and resolve complex data and platform issues in challenging enterprise environments Contribute to a supportive engineering culture focused on quality, delivery, and continuous improvement What We're Looking For This role is for a genuine practitioner who enjoys doing the work and raising standards around them. Essential Experience Significant hands-on experience as a Senior or Lead Data Engineer working on complex, enterprise-scale systems Strong Python and Spark skills with evidence of building and maintaining production data pipelines Deep understanding of the full data engineering lifecycle: ingestion, transformation, storage, serving, and reuse Strong experience designing integrations across diverse data sources, platforms, and legacy environments Experience building and supporting cloud-based data platforms, preferably within AWS environments Proven experience designing scalable data models and architectures Solid understanding of data governance, security, compliance, and operational controls Experience with modern engineering practices including source control, automated testing, CI/CD, infrastructure as code, and deployment automation Ability to communicate effectively with both highly technical and non-technical stakeholders Experience supporting machine learning or AI workloads through production-grade data engineering solutions Highly Desirable Strong AWS data platform experience (S3, Glue, EMR, Redshift, Athena, Lambda, Bedrock, SageMaker or equivalent) Experience operationalising machine learning models into production environments Experience with MLOps, model deployment, model monitoring, model lifecycle management, and automated validation processes Experience supporting Generative AI solutions, including RAG architectures, vector search, LLM integration, AI orchestration, or agentic workflows Databricks experience, including Unity Catalog, MLflow, Delta Lake, Lakehouse architecture, and AI tooling Experience working within secure, regulated, or government environments Exposure to large-scale enterprise data and AI platforms If you're passionate about building enterprise-scale data platforms, enabling AI adoption, and solving genuinely difficult engineering challenges, we'd love to hear from you. Apply now. Guidant, Carbon60, Lorien & SRG - The Vertage Group Portfolio are acting as an Employment Business in relation to this vacancy.
Oct 08, 2026
Full time
Lead Data Engineer (AI & Data Platforms) Must Be DV Clearable 5 Days Onsite Hands-on technical leadership building data and AI systems that actually work We're looking for a Lead Data Engineer to join a growing enterprise data and AI capability, playing a critical role in designing, building, and operating production-grade data platforms and AI-enabled solutions. This is not a line-management role . Instead, it is a senior, hands-on technical leadership position for someone with deep data engineering experience who leads through delivery, technical judgement, and engineering excellence rather than hierarchy. You will work across complex environments spanning legacy platforms, modern cloud services, advanced analytics, machine learning, and emerging AI technologies. The challenge isn't greenfield experimentation; it's building robust production systems, operationalising AI capabilities, improving what exists, and helping teams use data and AI safely, effectively, and at scale. We're particularly interested in engineers who have helped organisations establish the foundations for AI-led development, including data platforms, ML pipelines, governance frameworks, deployment processes, and production support models. What You'll Be Doing You'll act as a senior technical anchor for both data engineering and AI-enablement initiatives, contributing directly while guiding others through example. You will: Design, build, and enhance enterprise-scale data platforms, pipelines, and services Lead complex data engineering work end-to-end, from problem definition and exploration through build, testing, deployment, and operational support Build and maintain cloud-native data platforms that support analytics, machine learning, and AI workloads Develop robust data pipelines supporting both traditional analytics and AI/ML use cases Work directly with technical and non-technical stakeholders to translate operational problems into scalable data and AI solutions Design data models, integration patterns, and storage structures that support long-term maintainability and reusability Help establish engineering frameworks for AI-led development, including environments, CI/CD processes, testing strategies, governance controls, and deployment standards Support the operationalisation of machine learning and AI solutions into production environments Improve data sharing, onboarding of new data sources, and interoperability across teams and systems Evaluate and introduce new tools, frameworks, and technologies where they deliver genuine value Build robust, production-grade solutions rather than proofs of concept Treat metadata, lineage, observability, governance, data quality, and security as first-class engineering concerns Diagnose and resolve complex data and platform issues in challenging enterprise environments Contribute to a supportive engineering culture focused on quality, delivery, and continuous improvement What We're Looking For This role is for a genuine practitioner who enjoys doing the work and raising standards around them. Essential Experience Significant hands-on experience as a Senior or Lead Data Engineer working on complex, enterprise-scale systems Strong Python and Spark skills with evidence of building and maintaining production data pipelines Deep understanding of the full data engineering lifecycle: ingestion, transformation, storage, serving, and reuse Strong experience designing integrations across diverse data sources, platforms, and legacy environments Experience building and supporting cloud-based data platforms, preferably within AWS environments Proven experience designing scalable data models and architectures Solid understanding of data governance, security, compliance, and operational controls Experience with modern engineering practices including source control, automated testing, CI/CD, infrastructure as code, and deployment automation Ability to communicate effectively with both highly technical and non-technical stakeholders Experience supporting machine learning or AI workloads through production-grade data engineering solutions Highly Desirable Strong AWS data platform experience (S3, Glue, EMR, Redshift, Athena, Lambda, Bedrock, SageMaker or equivalent) Experience operationalising machine learning models into production environments Experience with MLOps, model deployment, model monitoring, model lifecycle management, and automated validation processes Experience supporting Generative AI solutions, including RAG architectures, vector search, LLM integration, AI orchestration, or agentic workflows Databricks experience, including Unity Catalog, MLflow, Delta Lake, Lakehouse architecture, and AI tooling Experience working within secure, regulated, or government environments Exposure to large-scale enterprise data and AI platforms If you're passionate about building enterprise-scale data platforms, enabling AI adoption, and solving genuinely difficult engineering challenges, we'd love to hear from you. Apply now. Guidant, Carbon60, Lorien & SRG - The Vertage Group Portfolio are acting as an Employment Business in relation to this vacancy.
AWS Data Engineer - Migration We're seeking a strong & hands-on AWS Data Engineering contractor, ASAP start, for an urgent replacement contract Rate: Up to £500-525 per day, Outside IR35 Working Patterns: Remote-first, London (up to 1 day p/w on-site). Contract: 3-6 months (likley extension) Sector: Financial Services About: We're supporting a major cloud transformation programme focused on migrating a large-scale legacy ETL estate consiting of several thousand batch jobs from Ab Initio to a modern, serverless AWS data platform. This is a hands-on Senior Data Engineer role where you'll play a key part in defining migration patterns and delivering production-ready AWS Glue solutions. Person Requirments: Strong AWS Data Engineer - ideally AWS Certified. Idelaly, you'll bring proven experience delivering Ab Initio AWS Glue (PySpark) migration programmes Strong hands-on AWS Data Engineering expertise, particularly AWS Glue , S3 , Athena and serverless data platforms. Advanced Python , PySpark and SQL skills. Strong understanding of converting Ab Initio transformations/reformat logic into scalable PySpark solutions. Experience building and optimising large-scale ETL/data pipeline solutions in AWS. Excellent Spark performance tuning capabilities, including troubleshooting data skew, partitioning, memory and load-related issues. Strong data warehousing and data modelling knowledge Strong comminication skills. Nice to Have Experience with Claude Code or AI-assisted code conversion tools. Amazon MWAA (Airflow) experience. AWS Certifications. Experience working on large-scale legacy modernisation programmes. Please apply now - this hiring process should be expected to finish by next week. Adam Akhtar
Oct 06, 2026
Full time
AWS Data Engineer - Migration We're seeking a strong & hands-on AWS Data Engineering contractor, ASAP start, for an urgent replacement contract Rate: Up to £500-525 per day, Outside IR35 Working Patterns: Remote-first, London (up to 1 day p/w on-site). Contract: 3-6 months (likley extension) Sector: Financial Services About: We're supporting a major cloud transformation programme focused on migrating a large-scale legacy ETL estate consiting of several thousand batch jobs from Ab Initio to a modern, serverless AWS data platform. This is a hands-on Senior Data Engineer role where you'll play a key part in defining migration patterns and delivering production-ready AWS Glue solutions. Person Requirments: Strong AWS Data Engineer - ideally AWS Certified. Idelaly, you'll bring proven experience delivering Ab Initio AWS Glue (PySpark) migration programmes Strong hands-on AWS Data Engineering expertise, particularly AWS Glue , S3 , Athena and serverless data platforms. Advanced Python , PySpark and SQL skills. Strong understanding of converting Ab Initio transformations/reformat logic into scalable PySpark solutions. Experience building and optimising large-scale ETL/data pipeline solutions in AWS. Excellent Spark performance tuning capabilities, including troubleshooting data skew, partitioning, memory and load-related issues. Strong data warehousing and data modelling knowledge Strong comminication skills. Nice to Have Experience with Claude Code or AI-assisted code conversion tools. Amazon MWAA (Airflow) experience. AWS Certifications. Experience working on large-scale legacy modernisation programmes. Please apply now - this hiring process should be expected to finish by next week. Adam Akhtar
Data Engineer Trading Platform Remote Up to £200k Plexus is working with a client in the DeFi trading space. They are a permission less, on-chain trading protocol allowing anyone to trade stocks, commodities, currencies and crypto through a fully transparent, auditable stack. They have raised $30M+ from a strong group of institutional and strategic backers. They are looking for a Data Engineer to own their monitoring, parameter systems and data infrastructure as the protocol scales. Role: Architecture and maintaining ingestion and transformation pipelines for on-chain events and market data. Implementing parameter models as reproducible, versioned code for review and deployment. Designing Grafana dashboards and alerting for protocol health and economic correctness. Building back testing and replay frameworks to validate parameter changes under stress scenarios. Requirements: Strong Python and SQL experience building production data pipelines. Hands-on AWS experience across S3, Athena/Glue, Redshift and ECS/Lambda. Proven ability to build monitoring systems with Grafana, including alerting and incident workflows. Experience productionising research logic with CI/CD, testing and reproducible environments. Benefits: Competitive compensation package. Flexible work arrangements. Professional development opportunities. If you're interested, please hit the "Easy Apply" button or get in touch
Sep 30, 2026
Full time
Data Engineer Trading Platform Remote Up to £200k Plexus is working with a client in the DeFi trading space. They are a permission less, on-chain trading protocol allowing anyone to trade stocks, commodities, currencies and crypto through a fully transparent, auditable stack. They have raised $30M+ from a strong group of institutional and strategic backers. They are looking for a Data Engineer to own their monitoring, parameter systems and data infrastructure as the protocol scales. Role: Architecture and maintaining ingestion and transformation pipelines for on-chain events and market data. Implementing parameter models as reproducible, versioned code for review and deployment. Designing Grafana dashboards and alerting for protocol health and economic correctness. Building back testing and replay frameworks to validate parameter changes under stress scenarios. Requirements: Strong Python and SQL experience building production data pipelines. Hands-on AWS experience across S3, Athena/Glue, Redshift and ECS/Lambda. Proven ability to build monitoring systems with Grafana, including alerting and incident workflows. Experience productionising research logic with CI/CD, testing and reproducible environments. Benefits: Competitive compensation package. Flexible work arrangements. Professional development opportunities. If you're interested, please hit the "Easy Apply" button or get in touch
Slalom is a global, human-centric business and technology consulting firm. We specialise in partnering with organisations that aspire to excellence, helping them tackle complex challenges and achieve transformative results through strategy, technology, and business transformation services. By prioritising people, Slalom creates a unique consulting experience, with a team of strategists and engineers delivering practical, end-to-end solutions that drive impactful outcomes for our clients. We empower people and organisations to dream bigger, move faster, and build better tomorrows for all. Slalom's Data Capability At Slalom, we believe that through our trusted relationships with our clients, we can create modern data solutions that drive results and improve the world. Interested in Strategy? Have a passion for Architecture? Want to work in a team that is pushing the forefront of the latest technology in the Engineering and AI space? We can offer you this. Slalom is agnostic when it comes to the technology we work with and we support clients in a range of data cloud partnershipsincludingAWS, Azure, Snowflake and Databricks to name but a few. We are interested in individuals who are passionate and curious about what is next. As a Senior Consultant AWS Data & AI Engineer at Slalom, you areaskilled engineerresponsible for delivering high-quality data solutions that generate measurable business value. Youdemonstratedeep technicalexpertisein AWS data services, combined with a keen understanding of client needs and the ability to collaborate productively within teams. Additionally, you play a key role in advancing our Data & Technology Capability. This position requiresproficiencyin designing and constructing robust data platforms, alongside the capacity to foster strong client partnerships. What will you do? Client Delivery & Technical Excellence Design, build, and implement scalable data engineering solutions on AWS, including data pipelines, ETL/ELT processes, and data integration frameworks. Develop andoptimizedata architectures using AWS services such as S3, Glue, Lambda, Redshift, Kinesis, EMR, Amazon OpenSearch Service, and graph databases such as Amazon Neptune, and related technologies. Ensure solutions follow AWS best practices for security, performance, cost optimization, and operational excellence. Collaborate with data architects, analysts, and business stakeholders to translate requirements into technical implementations. Use AI-assisted development tools appropriately to support engineering productivity, code quality, testing, and delivery. Mentor junior team members and contribute to building technical capability within project teams. Client Advisory & Relationship Building Act as a trusted advisor to client stakeholders, understanding their business challenges and recommendingappropriate datasolutions. Communicate technical concepts clearly to both technical and non-technical audiences. Contribute to client workshops, requirements gathering sessions, and solution design activities. Practice Development & Knowledge Sharing Stay current with AWS data engineering trends, services, and best practices. Contribute to the development of Slalom's data engineering accelerators, frameworks, and methodologies. Share knowledge through internal presentations, documentation, and mentoring. Participate in Slalom's learning culture and pursue continuous professional development. Whatyou'llbring Considerable experiencein data engineeringfocused on AWS data platforms and services. Strong hands-on experience withAWS data servicesincluding S3, Glue, Lambda, Redshift, Athena, EMR, Kinesis, Amazon OpenSearch Service, and graph databases such as Amazon Neptune, and related technologies. Proficiencyin programming languages such asPythonandSQL fordata processing and transformation. Experience designing and implementingETL/ELT pipelines, data integration patterns, and workflow orchestration. Understanding ofdata modelling concepts(dimensional modelling, data vault, normalized schemas) and when to apply them. Knowledge ofdata governance, data quality, and metadata managementprinciples. Experience withInfrastructure as Code(CloudFormation, Terraform, CDK) and CI/CD practices. Strong problem-solving skills and ability to work effectively in fast-paced consultingenvironments. Excellent communication and interpersonal skills, withdemonstratedability to work collaboratively with diverse teams. Client-facing consulting experiencewith ability to build rapport and credibility with stakeholders. AWS certificationssuch as AWS Certified Data Engineer - Associate, AWS Certified Solutions Architect - Associate, or AWS Certified Developer - Associate Experience withstreaming data architecturesand real-time analytics Familiaritywithdata platformssuch asSnowflake, Databricks is a bonus Experience with ML/AI engineering, including building or integrating production-grade machine learning or generative AI solutions. Experience with agentic development patterns, including tool use, workflow orchestration, and evaluation of agent behavior. Experience with semantic layers and ontology design, including defining consistent business concepts, relationships, and metadata for analytics and AI use cases. Relevant AWS AI certifications, such as AWS Certified AI Practitioner, AWS Certified Machine Learning Engineer - Associate, or AWS Certified Generative AI Developer - Professional. We have a question for you - and it's something we're passionate about. Can you imagine a world in which you can truly love your life and your work? Well, we have some good news - creating that world and making this vision a reality is what we get out of bed for; it's our north star. But what do we really mean when we talk about loving your life and your work? Let's look at the ways in which we help our team members to achieve this - and the 'how'. Deep connections, better outcome We have deep relationships with leading technology partners and they love us for our innovative and outcome based approach. Our people are passionate about solving our clients problems using the tech that's the best solution for them. What's more, we're there to work side-by-side with our client teams to enable them for success long after we've gone. We're all about momentum that outlasts us. Flexibility Life is busy, and we understand that. Our team often juggles work, family, personal commitments, and crucial client obligations. We prioritise supporting our people in balancing what matters to them while ensuring we meet our client commitments. Flexibility is key, as we sometimes need to adapt to meet client needs. This way, our team can work on high-impact projects they'll love, knowing they have the flexibility to manage their personal and professional lives effectively. People-first Great solutions start with great people. At our employee-led company, your voice matters, and we love to hear your feedback. By leading with kindness, empathy, and striving for equity, we create better experiences for everyone. Our culture encourages passion, adventure, adaptability, and diverse thinking. Inclusion, diversity, and equity are our top priorities, empowering our team to be their best selves. Together, we can create a great future by working collaboratively and supporting each other. Rewards There's no shying away from it - the compensation and benefits on offer have to be competitive too, right? We know that. That's why we have a dedicated team working with our leaders to ensure our packages are fair, competitive, and rewarding! Who are we We are Slalom! Slalom is a fiercely human business and technology consulting company that leads with outcomes to bring more value, in all ways, always. From strategy through delivery, our agile teams across 52 offices in 12 countries partner with clients to co-create powerful customer experiences, modern ways of working and meaningful impact. What sets us apart? We believe work should be challenging and fulfilling, not perfect, but possible. That's why we prioritise purpose, flexibility, connection and recognition so our people can thrive and love what they do, most days. We're honoured to be consistently recognised as a great place to work, including being one of Fortune's 100 Best Companies to Work for nine years running. Read more at Slalom prides itself on helping our team members thrive in their work and life. As a result, Slalom is proud to invest in our team members with competitive and innovative benefit programs and services that meet the unique needs of our diverse workforce. If you require any assistance with regards to reasonable adjustments during the recruitment process, please do not hesitate to contact us - we will always be happy to help.
Sep 30, 2026
Full time
Slalom is a global, human-centric business and technology consulting firm. We specialise in partnering with organisations that aspire to excellence, helping them tackle complex challenges and achieve transformative results through strategy, technology, and business transformation services. By prioritising people, Slalom creates a unique consulting experience, with a team of strategists and engineers delivering practical, end-to-end solutions that drive impactful outcomes for our clients. We empower people and organisations to dream bigger, move faster, and build better tomorrows for all. Slalom's Data Capability At Slalom, we believe that through our trusted relationships with our clients, we can create modern data solutions that drive results and improve the world. Interested in Strategy? Have a passion for Architecture? Want to work in a team that is pushing the forefront of the latest technology in the Engineering and AI space? We can offer you this. Slalom is agnostic when it comes to the technology we work with and we support clients in a range of data cloud partnershipsincludingAWS, Azure, Snowflake and Databricks to name but a few. We are interested in individuals who are passionate and curious about what is next. As a Senior Consultant AWS Data & AI Engineer at Slalom, you areaskilled engineerresponsible for delivering high-quality data solutions that generate measurable business value. Youdemonstratedeep technicalexpertisein AWS data services, combined with a keen understanding of client needs and the ability to collaborate productively within teams. Additionally, you play a key role in advancing our Data & Technology Capability. This position requiresproficiencyin designing and constructing robust data platforms, alongside the capacity to foster strong client partnerships. What will you do? Client Delivery & Technical Excellence Design, build, and implement scalable data engineering solutions on AWS, including data pipelines, ETL/ELT processes, and data integration frameworks. Develop andoptimizedata architectures using AWS services such as S3, Glue, Lambda, Redshift, Kinesis, EMR, Amazon OpenSearch Service, and graph databases such as Amazon Neptune, and related technologies. Ensure solutions follow AWS best practices for security, performance, cost optimization, and operational excellence. Collaborate with data architects, analysts, and business stakeholders to translate requirements into technical implementations. Use AI-assisted development tools appropriately to support engineering productivity, code quality, testing, and delivery. Mentor junior team members and contribute to building technical capability within project teams. Client Advisory & Relationship Building Act as a trusted advisor to client stakeholders, understanding their business challenges and recommendingappropriate datasolutions. Communicate technical concepts clearly to both technical and non-technical audiences. Contribute to client workshops, requirements gathering sessions, and solution design activities. Practice Development & Knowledge Sharing Stay current with AWS data engineering trends, services, and best practices. Contribute to the development of Slalom's data engineering accelerators, frameworks, and methodologies. Share knowledge through internal presentations, documentation, and mentoring. Participate in Slalom's learning culture and pursue continuous professional development. Whatyou'llbring Considerable experiencein data engineeringfocused on AWS data platforms and services. Strong hands-on experience withAWS data servicesincluding S3, Glue, Lambda, Redshift, Athena, EMR, Kinesis, Amazon OpenSearch Service, and graph databases such as Amazon Neptune, and related technologies. Proficiencyin programming languages such asPythonandSQL fordata processing and transformation. Experience designing and implementingETL/ELT pipelines, data integration patterns, and workflow orchestration. Understanding ofdata modelling concepts(dimensional modelling, data vault, normalized schemas) and when to apply them. Knowledge ofdata governance, data quality, and metadata managementprinciples. Experience withInfrastructure as Code(CloudFormation, Terraform, CDK) and CI/CD practices. Strong problem-solving skills and ability to work effectively in fast-paced consultingenvironments. Excellent communication and interpersonal skills, withdemonstratedability to work collaboratively with diverse teams. Client-facing consulting experiencewith ability to build rapport and credibility with stakeholders. AWS certificationssuch as AWS Certified Data Engineer - Associate, AWS Certified Solutions Architect - Associate, or AWS Certified Developer - Associate Experience withstreaming data architecturesand real-time analytics Familiaritywithdata platformssuch asSnowflake, Databricks is a bonus Experience with ML/AI engineering, including building or integrating production-grade machine learning or generative AI solutions. Experience with agentic development patterns, including tool use, workflow orchestration, and evaluation of agent behavior. Experience with semantic layers and ontology design, including defining consistent business concepts, relationships, and metadata for analytics and AI use cases. Relevant AWS AI certifications, such as AWS Certified AI Practitioner, AWS Certified Machine Learning Engineer - Associate, or AWS Certified Generative AI Developer - Professional. We have a question for you - and it's something we're passionate about. Can you imagine a world in which you can truly love your life and your work? Well, we have some good news - creating that world and making this vision a reality is what we get out of bed for; it's our north star. But what do we really mean when we talk about loving your life and your work? Let's look at the ways in which we help our team members to achieve this - and the 'how'. Deep connections, better outcome We have deep relationships with leading technology partners and they love us for our innovative and outcome based approach. Our people are passionate about solving our clients problems using the tech that's the best solution for them. What's more, we're there to work side-by-side with our client teams to enable them for success long after we've gone. We're all about momentum that outlasts us. Flexibility Life is busy, and we understand that. Our team often juggles work, family, personal commitments, and crucial client obligations. We prioritise supporting our people in balancing what matters to them while ensuring we meet our client commitments. Flexibility is key, as we sometimes need to adapt to meet client needs. This way, our team can work on high-impact projects they'll love, knowing they have the flexibility to manage their personal and professional lives effectively. People-first Great solutions start with great people. At our employee-led company, your voice matters, and we love to hear your feedback. By leading with kindness, empathy, and striving for equity, we create better experiences for everyone. Our culture encourages passion, adventure, adaptability, and diverse thinking. Inclusion, diversity, and equity are our top priorities, empowering our team to be their best selves. Together, we can create a great future by working collaboratively and supporting each other. Rewards There's no shying away from it - the compensation and benefits on offer have to be competitive too, right? We know that. That's why we have a dedicated team working with our leaders to ensure our packages are fair, competitive, and rewarding! Who are we We are Slalom! Slalom is a fiercely human business and technology consulting company that leads with outcomes to bring more value, in all ways, always. From strategy through delivery, our agile teams across 52 offices in 12 countries partner with clients to co-create powerful customer experiences, modern ways of working and meaningful impact. What sets us apart? We believe work should be challenging and fulfilling, not perfect, but possible. That's why we prioritise purpose, flexibility, connection and recognition so our people can thrive and love what they do, most days. We're honoured to be consistently recognised as a great place to work, including being one of Fortune's 100 Best Companies to Work for nine years running. Read more at Slalom prides itself on helping our team members thrive in their work and life. As a result, Slalom is proud to invest in our team members with competitive and innovative benefit programs and services that meet the unique needs of our diverse workforce. If you require any assistance with regards to reasonable adjustments during the recruitment process, please do not hesitate to contact us - we will always be happy to help.
This is an exciting opportunity where we're exploring local Sr Lead Security Engineering talent who need flexibility, with the potential to present qualified candidates to managers for part-time or job-share roles. Part-time hours where two people share the responsibilities. We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Site Reliability Engineer at JPMorgan Chase within the Commercial & Investment Bank - Markets - Commodities Technology, you hold a technical leadership role in your team, demonstrate strong knowledge across multiple technical domains, and advise others on the technical and business issues facing them. You will will set the vision, strategy, and operating model for our SRE transformation - enabling our business-aligned support teams to deliver higher reliability, stronger resilience, and a measurably better end-user experience across the board. Job responsibilities Defines the SRE vision, north-star outcomes, and multi-year roadmap for the Production Management team, aligned to both CIB and JPM Global Technology priorities. Establishes the SRE operating model across global regions (ways of working, intake, prioritization, engagement with engineering teams and production support). Partners with business-aligned Production Support leads to embed SRE practices consistently and act as a force multiplier - coaching them on reliability thinking, prioritization, and "engineering out" operational load. Builds and develops a small, high-impact core SRE team (and/or virtual SRE community of practice) that scales reliability improvements across many application flows. Defines and implements standards for: Service cataloging, SLO/SLI frameworks and error budgets, incident response maturity, blameless post-incident reviews, resiliency patterns, capacity, performance, and scalability engineering. Drives service reviews with evidence-based reporting (availability, latency, incident trends, MTTR/MTTD, change failure rate, customer impact). Champions AI adoption and deliver AI-enabled capabilities to reduce operational toil and improve speed/quality of response. Sets direction for observability across logs/metrics/traces, including instrumentation standards, golden signals, and end-user journey monitoring. Improves alert quality and routing: reduce false positives, improve actionable alerts, and tighten feedback loops to engineering teams. Builds strong partnerships with application development teams, platform/infrastructure partners, and governance functions. Communicates clearly and credibly at all levels-from engineers to senior technology and business stakeholders. Uses enterprise-authorized AI capabilities within the work environment to accelerate major-incident triage, troubleshooting, and post-incident analysis, validating outputs and handling operational data according to sensitivity and security requirements. Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices (e.g., CI/CD quality checks, test/validation automation, and operational readiness), ensuring traceability/auditability, resiliency, and security controls. Required qualifications, capabilities, and skills 10+ years of experience in technology support, production/application support, DevOps, or infrastructure management. Demonstrated experience leading SRE/reliability engineering or production engineering transformations in a complex enterprise environment. Strong engineering background: ability to design, build, and deliver automation and reliability solutions. Fluency & expertise in Python Deep practical knowledge of: SLOs/SLIs, error budgets, incident management, postmortems, observability design across metrics/logs/traces and distributed systems troubleshooting, resilience engineering, performance/capacity management, and change risk reduction. Proficiency and experience with telemetry (logs/metrics/traces) collection using tools and standards such as Prometheus, Open Telemetry, Datadog, Dynatrace, Splunk. Experience delivering automation at scale (scripting, workflow automation, runbook automation, CI/CD-integrated guardrails). Proven leadership skills: influencing without authority, coaching leaders, and building communities of practice. Strong judgment around risk, security, and controls-especially when applying AI to production workflows. Demonstrated experience using enterprise-authorized AI capabilities within the work environment to improve SRE workflows (e.g., incident investigation support and knowledge capture) with strong validation habits and awareness of data sensitivity. Ability to evaluate AI-assisted operational recommendations for correctness and risk, define appropriate guardrails for team usage, and ensure outcomes align to resiliency and security expectations. Preferred qualifications, capabilities, and skills Familiarity with Athena / prior experience in Athena Your Pathway to Jobsharing at JPMorgan - IT'S A 2 BRAINER! At JPMorgan we are passionate about supporting different ways of working to support our talent in the flexibility they need. We know that Jobshare is a fantastic way to hire talent for the firm that offers both the flexibility that you need whilst providing the consistency that our business requires. Jobshare is 2 people working part time hours with full time powers. This role is part of a Jobshare opportunity and therefore a part-time role at 19hours
Sep 23, 2026
Full time
This is an exciting opportunity where we're exploring local Sr Lead Security Engineering talent who need flexibility, with the potential to present qualified candidates to managers for part-time or job-share roles. Part-time hours where two people share the responsibilities. We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Site Reliability Engineer at JPMorgan Chase within the Commercial & Investment Bank - Markets - Commodities Technology, you hold a technical leadership role in your team, demonstrate strong knowledge across multiple technical domains, and advise others on the technical and business issues facing them. You will will set the vision, strategy, and operating model for our SRE transformation - enabling our business-aligned support teams to deliver higher reliability, stronger resilience, and a measurably better end-user experience across the board. Job responsibilities Defines the SRE vision, north-star outcomes, and multi-year roadmap for the Production Management team, aligned to both CIB and JPM Global Technology priorities. Establishes the SRE operating model across global regions (ways of working, intake, prioritization, engagement with engineering teams and production support). Partners with business-aligned Production Support leads to embed SRE practices consistently and act as a force multiplier - coaching them on reliability thinking, prioritization, and "engineering out" operational load. Builds and develops a small, high-impact core SRE team (and/or virtual SRE community of practice) that scales reliability improvements across many application flows. Defines and implements standards for: Service cataloging, SLO/SLI frameworks and error budgets, incident response maturity, blameless post-incident reviews, resiliency patterns, capacity, performance, and scalability engineering. Drives service reviews with evidence-based reporting (availability, latency, incident trends, MTTR/MTTD, change failure rate, customer impact). Champions AI adoption and deliver AI-enabled capabilities to reduce operational toil and improve speed/quality of response. Sets direction for observability across logs/metrics/traces, including instrumentation standards, golden signals, and end-user journey monitoring. Improves alert quality and routing: reduce false positives, improve actionable alerts, and tighten feedback loops to engineering teams. Builds strong partnerships with application development teams, platform/infrastructure partners, and governance functions. Communicates clearly and credibly at all levels-from engineers to senior technology and business stakeholders. Uses enterprise-authorized AI capabilities within the work environment to accelerate major-incident triage, troubleshooting, and post-incident analysis, validating outputs and handling operational data according to sensitivity and security requirements. Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices (e.g., CI/CD quality checks, test/validation automation, and operational readiness), ensuring traceability/auditability, resiliency, and security controls. Required qualifications, capabilities, and skills 10+ years of experience in technology support, production/application support, DevOps, or infrastructure management. Demonstrated experience leading SRE/reliability engineering or production engineering transformations in a complex enterprise environment. Strong engineering background: ability to design, build, and deliver automation and reliability solutions. Fluency & expertise in Python Deep practical knowledge of: SLOs/SLIs, error budgets, incident management, postmortems, observability design across metrics/logs/traces and distributed systems troubleshooting, resilience engineering, performance/capacity management, and change risk reduction. Proficiency and experience with telemetry (logs/metrics/traces) collection using tools and standards such as Prometheus, Open Telemetry, Datadog, Dynatrace, Splunk. Experience delivering automation at scale (scripting, workflow automation, runbook automation, CI/CD-integrated guardrails). Proven leadership skills: influencing without authority, coaching leaders, and building communities of practice. Strong judgment around risk, security, and controls-especially when applying AI to production workflows. Demonstrated experience using enterprise-authorized AI capabilities within the work environment to improve SRE workflows (e.g., incident investigation support and knowledge capture) with strong validation habits and awareness of data sensitivity. Ability to evaluate AI-assisted operational recommendations for correctness and risk, define appropriate guardrails for team usage, and ensure outcomes align to resiliency and security expectations. Preferred qualifications, capabilities, and skills Familiarity with Athena / prior experience in Athena Your Pathway to Jobsharing at JPMorgan - IT'S A 2 BRAINER! At JPMorgan we are passionate about supporting different ways of working to support our talent in the flexibility they need. We know that Jobshare is a fantastic way to hire talent for the firm that offers both the flexibility that you need whilst providing the consistency that our business requires. Jobshare is 2 people working part time hours with full time powers. This role is part of a Jobshare opportunity and therefore a part-time role at 19hours
