Adria Solutions
Manchester, Lancashire
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 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
Lorien
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.
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.
