13 jobs found

DataOps Engineer - Data Science Operations page is loaded DataOps Engineer - Data Science Operationslocations: London, UKtime type: Full timeposted on: Posted Yesterdayjob requisition id: R1227At Castleton Commodities International (CCI), we are redefining how data and technology shape the future of energy trading. Our Data Science & Technology team is at the forefront of this transformation, developing systems and innovative tools that empower our front-office teams to better understand market dynamics, forecast prices, and manage risk. Our Data Science Operations team is integral to our mission, ensuring the seamless ingestion and management of data across our platforms. The DataOps Engineer will assist with all aspects of data - from data architecture design to on-going data management and will have significant exposure to our Commercial investing teams globally. This position will play an integral role as the firm continues to expand its use of data for advanced analytics and other commercial purposes. Responsibilities: Execute data architecture and data management projects for existing data sources, ensuring alignment with business and technical requirements. Design, enhance, and maintain market data platforms using Python, optimizing for scalability and performance. Manage the end-to-end data ingestion process, including extraction, transformation, loading (ETL), and data publishing for investment and commercial teams. Own and continuously improve the process of mapping, standardizing, and normalizing fundamental analytics data to support consistent usage across business functions. Implement automated workflows for error handling and develop data quality analysis to proactively identify and address systemic issues. Prioritize and resolve critical market data issues based on business impact and user-reported concerns. Coordinate with technology and business stakeholders to align goals, timelines, and deliverables for strategic big data initiatives. Serve as a liaison with commercial (trading) teams to translate their needs regarding data flow, architecture, and the investment process into functional data requirements. Provide operational support for market data platforms, handling performance tuning, incident response, and user assistance. Ensure platform stability and resilience by developing and maintaining operational runbooks, standard operating procedures (SOPs), and incident response protocols. Qualifications: Bachelor's degree in Computer Science, Mathematics, Physics, Engineering or related field of study. 5+ years' experience in data operations production environment, ideally in financial services or energy commodities. Proficient in Python programming and its libraries - Pandas, NumPy, etc. Experience with front-end technologies such as HTML, CSS, JavaScript, and modern front-end frameworks (e.g., React, Angular) is a plus. Prior experience with Snowflake columnar database and ability to design and optimize complex SQL queries. Proficient in using version control systems like Git to manage code repositories effectively. Strong analytical and problem-solving skills to tackle complex technical challenges. Proficiency in debugging and performance optimization techniques. Understanding of the software development lifecycle, from requirements analysis to testing and deployment. Ability to work effectively in a fast-paced, dynamic and high-intensity environment including open-floor plan if applicable to the position, with timely responsiveness and the ability to work beyond normal business hours when required. Employee Programs & Benefits: CCI offers competitive benefits and programs to support our employees, their families and local communities. These include: Competitive comprehensive medical, dental, retirement and life insurance benefits Employee assistance & wellness programs Parental and family leave policies CCI in the Community: Each office has a Charity Committee and as a part of this program employees are allocated 2 days annually to volunteer at the selected charities. Charitable contribution match program Tuition assistance & reimbursement Quarterly Innovation & Collaboration Awards Employee discount program, including access to fitness facilities Competitive paid time off Continued learning opportunitiesVisit to learn more! Commodities International is a leading global energy commodities merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in, and develop, select commodity infrastructure assets. This fully integrated platform has generated strong risk-adjusted returns for our investors since our formation.

A total cash package of up to £110,000 comprising of a base salary of £82,005 We are a dynamic consulting firm, focused on delivering sustainable change. We ensure our clients succeed in their long-term goals by helping them turn their strategy into action through exceptional delivery and a commitment to establishing a culture of change. Clients like what we do and how we work, and we are looking for people to join the Moorhouse team. We pride ourselves on being proactive, collaborative, and straightforward team players. We work efficiently and collaboratively as a team and both honesty and integrity are key to this. In return you will be part of a supportive and high-performing team that shares the workload, looks after each other and celebrates success together. You can be assured of an exciting opportunity that will help you grow your skills through meaningful challenges and equip you with skills, experience and knowledge that can help organisations respond to the turbulence, change and opportunity that will define the future of work. We encourage behaviours that promote transparency, collaboration and achievement of shared goals. Data Science at Moorhouse Our Data Science capability is a growing and strategically significant part of Moorhouse. We help organisations unlock the value of their data by combining deep technical expertise with the consulting skills needed to drive real-world change. Our team works across the full data and analytics lifecycle,from defining strategy and enabling data-driven cultures, to building advanced analytical models and delivering digital products that embed predictive insight into everyday decision-making. We partner with clients across multiple sectors, including healthcare, energy and utilities, life sciences, financial services and TMT. Much of our work today focuses on developing and deploying analytical tools and web-based products that deliver forecasting, optimisation, and automated insight. Our projects span machine learning, statistical modelling, data engineering, data visualisation and MLOps, always with a focus on driving tangible business outcomes. As demand for digital and AI-enabled transformation continues to grow, our Data Science team is expandingand contributing to some of the most impactful programmes across the firm. Responsibilities Why join the Data Science team at Moorhouse? We are seeking a hands-on, technically focused Manager to join the Data Science function, who will lead the delivery of complex data science and digital product projects. While there will be opportunities to contribute to business growth and propositions, the key component of this role is strong technical delivery : architecting solutions, guiding teams, and ensuring the highest-quality output. This role complements another Manager in the team who is focused on proposition development and commercial growth. You will bring the deep engineering and delivery expertise necessary to ensure our solutions are robust, scalable and production-ready. In this role, you will have the opportunity to: Lead complex end-to-end delivery of data science and digital product solutions Lead the delivery of high-impact projects involving machine learning, forecasting, optimisation and data-driven digital products. Design and architect analytical solutions, including modelling approaches, data pipelines, integration patterns and deployment frameworks. Promote delivery excellence, engineering discipline and best-practice coding standards across teams. Be the technical leadership on DevOps/MLOps Implement and embed CI/CD pipelines, automated testing frameworks, containerisation and monitoring. Guide cloud architecture and infrastructure-as-code approaches (AWS, Azure, GCP). Encourage best practices for operationalising machine learning models at scale. Lead multidisciplinary teams with confidence Coach, mentor and support junior team members, ensuring they deliver high-quality technical work. Foster engineering maturity and support the development of technical capability across the team. Engage with senior stakeholders Translate technical detail into actionable insights and recommendations for clients. Build trusted relationships with leaders across multiple sectors. Support commercial and proposition development Provide technical input into proposals and bids. Contribute to refining our Data Science and AI propositions. Essential skills What are we looking for? We are seeking candidates with 6-8+ years of experience in data science, data engineering, analytics or AI product delivery, with a strong emphasis on hands-on technical leadership. Deep Technical Delivery Expertise Advanced proficiency in Python and SQL ; experience designing and delivering production-grade solutions. Operationalisation of machine learning models, forecasting tools, optimisation algorithms or analytical applications. Experience designing data pipelines, ETL workflows, APIs and data integration approaches. Automated testing (unit, integration, data validation, ML testing) Infrastructure-as-code (Terraform, ARM, CloudFormation) Monitoring and observability Experience with cloud ecosystems (Azure, AWS, GCP, Snowflake, Databricks). Strong understanding of software engineering fundamentals and modern development practices. Leadership & Consulting Capability Proven ability to lead delivery of complex technical programmes. Strong people leadership and mentoring capabilities. Excellent communication skills and ability to engage senior stakeholders. Collaborative mindset and commitment to high-quality client delivery. What we can offer you: A total cash package of up to £110,000 comprising of a base salary of £82,005 and a combination of personal and company bonuses that are paid every six months. 25 days annual leave increasing by one day for every full year of service to a maximum of 30 days with the option to buy or sell up to five days of annual leave per year. Life Assurance, Private Medical Insurance, Group Personal Pension Scheme and a range of discounted lifestyle and well-being benefits through Perkbox. A culture where you will not need to compete with others because of promotion quotas or the typical distribution curves that govern performance management in other organisations. We recognise and reward performance consistently and transparently across the firm so that everyone knows where they stand. We offer flexible working arrangements with our offices near Liverpool Street although you can expect to spend some time as part of a team onUKclient sites.Wesupport flexibility wherever possible. Moorhouse is proud to be an equal opportunities employer, and our values underpin a working environment that is inclusive for all those who work for us. We encourage people to bring their whole selves to work, contribute ideas, take the initiative and be responsible for their impact on others internally and externally. We value your privacy

We are Ataccama, and we are on a mission to power a better future with data. Our product enables both technical and less technical 'data people' across their organizations to create high-quality, governed, safe, and reusable data products. It's what made us a Leader in the Gartner Magic Quadrant for Data Quality Solutions , and what inspired Bain Capital Tech Opportunities to invest in our future growth. Our vision is to be the leading AI-powered cloud data management company and to do that, we're making Ataccama a great place to work and grow. Our people are located across the globe. They succeed by collaborating as a team and thrive in our company culture defined by these core values: Challenging Fun ONE Team Customer Centric Candid and Caring Aim High Senior Sales Engineer - Your Challenge As a Senior Sales Engineer, you will work closely with Account Executives to drive sales engineering activities across the entire deal lifecycle. This role requires adaptability, deep technical expertise, and the ability to create customized solutions that resonate with clients across diverse industries. Sales Engineering Lifecycle Management: Oversee and execute all sales engineering activities throughout the deal lifecycle, from initial engagement to deal closure. Customized Client Solutions: Develop presentations and configure demonstrations to meet the specific needs of the audience, tailoring it to each prospect's industry and unique needs. Spearhead Proof of Concepts (POCs): Lead and execute Proof of Concepts (POCs), demonstrating the platform's effectiveness in addressing client-specific business pains and customizing the platform to technical requirements. Advanced Client Engagement: Lead in-depth technical discussions with clients, effectively aligning Ataccama's solutions with their needs. AI Feature Champion: Actively showcase and articulate the value of Ataccama's expanding AI capabilities (e.g., for data quality, governance, and master data management) in all presentations and demonstrations. Industry and Product Expertise: Maintain a thorough understanding of relevant technologies, competitors, business cases and industry specifics to effectively align solutions. Collaboration with Account Executives: Work closely with Account Executives, providing technical insights and support to ensure a cohesive sales strategy within the given territory. Professional Development: Maintain a commitment to continuous learning and development, staying ahead of industry trends and Ataccama product advancements Is This You? 5+ years experience in a client-facing technical role (Sales Engineering, Solutions Consulting, etc.) Experience working with Data Quality, Data Observability, Data Governance or Master Data Management tools Proficient in SQL, data pipelines, Databricks/Snowflake, APIs, and preferably programming experience ideally in Python. Proven success working with large enterprises with complex technical environments Experience leveraging Python for AI/ML prototyping or data science tasks is a strong plus. Strong problem-solving and creative thinking skills Perks & Benefits Long-Term Incentive Program 5 sick days and 25 days of vacation, with the option to request additional Enhanced Time-Off days when needed The Global Family Support Program - a paid leave program to help all parents focus on the new addition to their family Pension plan "Bring Your Friend" referral program Flexible working hours & hybrid work setup Health insurance provided by Vitality Online courses & company access to Udemy to hone your skills Conference tickets to the best industry events of the year Cycle to work scheme Work equipment Company laptop Company mobile phone At Ataccama, our core values are Candid & Caring, so we are upfront about our process and details that are important to you. We sometimes use AI tools to help us with things like reviewing applications, taking notes from screening conversations, scheduling interviews, or supporting assessments. These tools make the process smoother and fairer - but don't worry, they never make the final decision. Every hiring decision is made by our Talent Acquisition Partners and Hiring Managers, with AI only acting as a helpful assistant. We believe technology should support the process, not replace the human touch. We currently use AI-assisted tools - Metaview for interview notes and Lever Talent Fit to help highlight key experience. While we highly value cooperation with all our business partners, we don't accept unsolicited resumes from any sources other than directly from a candidate. We reserve the right not to pay any fee for sending an unsolicited offer containing the details or resume of a job candidate, even if the relevant candidate is employed by our company.

Data Science Manager page is loaded Data Science Managerremote type: Hybridlocations: Belfast - 20 Adelaide Streetposted on: Posted Todayjob requisition id: JR-Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation and navigate constant change. Through a combination of strategy, expertise and creativity, we help clients accelerate operational, digital and cultural transformation, enabling the change they need to own their future. Join our team as the expert you are now and create your future. Data Science Manager We're seeking a Data Science Manager to join the Data Science & Machine Learning team in our Commercial Digital practice, where you'll lead advanced analytics initiatives that transform how Fortune 500 companies make decisions across Financial Services, Manufacturing, Energy & Utilities, and other commercial industries.Managers play a vibrant, integral role at Huron. Their invaluable knowledge reflects in the projects they manage and the teams they lead. Known for building long-standing partnerships with clients, they collaborate with colleagues to solve their most important challenges. Our Managers also spend significant time mentoring junior staff on the engagement team-sharing expertise, feedback, and encouragement. This promotes a culture of respect, unity, collaboration, and personal achievement.This isn't a reporting role or a dashboard factory-you'll own the full analytics lifecycle from hypothesis formulation through insight delivery, while leading and developing a team of data scientists and analysts. You'll work on problems that matter: experimental designs that validate multi-million-dollar strategies, predictive models that surface hidden patterns in complex data, and deep learning pipelines that extract signal from unstructured text, images, and time-series. Our clients are Fortune 500 companies looking for partners who can find the signal in the noise and tell the story that drives action.The variety is real. In your first year, you might lead a customer segmentation and lifetime value analysis for a financial services firm, design and analyze a pricing experiment for a global manufacturer, and build an agentic anomaly detection system for a utility company's operational data-all while developing the next generation of data science talent at Huron. If you thrive on rigorous analysis, clear communication of complex findings, and building high-performing teams, this role is for you.# What You'll Do Lead and mentor junior data scientists and analysts -provide technical guidance, review analytical approaches and code, and support professional development. Foster a culture of intellectual curiosity, rigorous methodology, and clear communication within the team. Manage complex multi-workstream analytics projects -oversee project planning, resource allocation, and delivery timelines. Ensure analyses meet quality standards and client expectations while maintaining methodological rigor. Design and execute end-to-end data science workflows -from problem framing and hypothesis development through exploratory analysis, modeling, validation, and insight delivery. Own the analytical approach and ensure conclusions are defensible. Lead development of both traditional statistical and modern AI-powered analyses -including regression, classification, clustering, causal inference, A/B testing, and modern deep learning approaches using embeddings, transformer architectures, and foundation models for text, time-series, and multimodal analysis. Build predictive and prescriptive models that drive business decisions-customer segmentation, churn prediction, demand forecasting, pricing optimization, risk scoring, and operational efficiency analysis for commercial enterprises. Translate complex analytical findings into actionable insights -create compelling data narratives, develop executive-ready presentations, and communicate technical results to non-technical stakeholders in ways that drive decisions. Serve as a trusted advisor to clients -build long-standing partnerships, deeply understand business problems, formulate the right analytical questions, and deliver insights that create measurable value. Contribute to practice development -participate in business development activities, develop reusable analytical frameworks and methodologies, and help shape the technical direction of Huron's DSML capabilities.# Required Qualifications 5+ years of hands-on experience conducting data science and advanced analytics -not just ad-hoc analysis, but structured analytical projects that drove business decisions. You've framed problems, developed hypotheses, analyzed data, and delivered insights that created measurable impact. Experience leading and developing technical teams -including coaching, mentorship, methodology review, and performance management. Demonstrated ability to build high-performing teams and develop junior talent. Strong Python and SQL programming skills with deep experience in the data science ecosystem (Pandas, NumPy, Scikit-learn, statsmodels, visualization libraries). Comfortable writing production-quality code, not just notebooks. Solid foundation in statistics and machine learning : hypothesis testing, regression analysis, classification, clustering, experimental design, causal inference, and understanding of when different approaches are appropriate for different questions. Experience with deep learning and modern neural architectures -understanding of transformer models, embeddings, transfer learning, and how to leverage foundation models for analytical tasks. You know when ML approaches add value over classical methods, and how to integrate them into rigorous analytical workflows. Proficiency with data platforms : Microsoft Fabric, Snowflake, Databricks, or similar cloud analytics environments. You're comfortable working with large datasets and can optimize queries for performance. Exceptional communication and data storytelling skills -ability to distill complex analyses into clear narratives, create compelling visualizations, lead client meetings, and build trusted relationships with executive audiences. This is non-negotiable. Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or related quantitative field (or equivalent practical experience). Flexibility to work in a hybrid model with periodic travel to client sites as needed.# Preferred Qualifications Experience in Financial Services, Manufacturing, or Energy & Utilities industries. Background in experimental design, A/B testing, and causal inference methodologies-including propensity score matching, difference-in-differences, or instrumental variables. Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and neural architectures-including transformers, attention mechanisms, and fine-tuning pretrained models for NLP, time-series, or tabular data applications. Experience building AI-assisted analytical workflows-leveraging foundation model APIs, vector databases, and retrieval systems to accelerate insight extraction from unstructured data. Experience with Bayesian methods, probabilistic programming (PyMC, NumPyro, etc.), or uncertainty quantification in business contexts. Strong visualization and data interface design and development skills using programmatic visualization libraries (Plotly, Altair, D3). Proficiency with AI-assisted rapid data application development using Cursor, Lovable, v0, etc. Experience with time-series analysis, forecasting methods (ARIMA, Prophet, neural forecasting), and demand planning applications. Cloud certifications (Azure Data Scientist, Databricks ML Associate, AWS ML Specialty). Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new

Vice President, Private Credit Investment Analytics Pantheon has been at the forefront of private markets investing for more than 40 years, earning a reputation for an innovative approach to investing in secondaries, co investments, and primary fund investments, as well as capital formation across commingled funds, evergreen vehicles and customized solutions. Pantheon currently manages approximately $82.3 billion in AUM across all its strategies, serving more than 750 institutional and 638 private wealth clients worldwide. The Vice President of Investment Analytics (Private Credit) will lead the development of Pantheon's private credit data and intelligence capability, transforming investment data into structured, decision ready insight for Portfolio Management teams. This role sits at the intersection of Investment, Data & Operations, and will focus on strengthening the firm's ability to generate consistent, comparable, and actionable intelligence from credit portfolio data - across funds, GPs, structures, and geographies. The VP will architect and operate scalable analytical frameworks that standardize how private credit data is defined, sourced, governed, and translated into insight. The role will partner closely with Investment Data Operations and Data Engineering teams to embed credit analytics into Pantheon's evolving data platforms, reducing reliance on bespoke spreadsheets and increasing transparency, comparability, and confidence. This is a high impact opportunity to shape Pantheon's private credit intelligence capability at a time of significant growth and platform transformation. Key Responsibilities Build private credit investment analytics across Pantheon to help evaluate and monitor investments. Act as a senior analytics partner to Investment and Portfolio Management teams, translating complex investment needs into structured data requirements and analytical frameworks. Own the definition, sourcing, and validation of investment relevant datasets, ensuring analytical outputs are complete, comparable, and decision ready. Deliver differentiated, investment grade insights by combining internal investment operations data with GP reported and external market data, moving beyond descriptive reporting to comparative, diagnostic, and thematic analysis. Serve as the primary data and analytics interface with GPs and external data/technology providers, shaping data standards, templates, and requirements to improve transparency, coverage, and usability. Operate Investment Analytics as a business facing function with a product mindset, creating a roadmap that prioritises initiatives based on investment impact, adoption, and measurable decision enablement. Lead, develop, and mentor a high performing Investment Analytics team, fostering disciplined delivery and strong stakeholder relationships. Knowledge & Experience Required Significant experience in private markets, with strong exposure to private credit, portfolio data, analytics or investment operations. Deep understanding of private credit structures, performance drivers, and portfolio monitoring. Strong analytical mindset with experience supporting investment or portfolio decision making. Strong understanding of data governance, comparability challenges, and portfolio transparency. Demonstrated ability to operate at both strategic and hands on levels. Proven ability to partner effectively with investment professionals and influence senior stakeholders. Strong written and verbal communication skills; able to articulate complex information clearly and concisely. Track record of delivering high quality outputs under tight timelines. Experience leading and developing teams in a collaborative environment. Experience with working with 3rd party providers, data vendors & offshore teams. Professional qualification (CFA, ACA, ACCA, IMC) or equivalent experience preferred but not essential. Familiarity with modern data environments and analytics tools (e.g., Power BI, SQL, Python, Databricks, Snowflake). Experience systemizing investment analytics within centralized data platforms. Exposure to automation or advanced analytical techniques to enhance portfolio monitoring. Demonstrated comfort integrating AI tools into daily analytical workflows (e.g., structured research, synthesis, data interrogation). Ability to evaluate AI outputs critically, refine prompts, and build repeatable AI assisted workflows. This job description is not to be construed as an exhaustive statement of duties, responsibilities, or requirements. You may be required to perform other job related duties as reasonably requested by your manager. Pantheon is an Equal Opportunities employer, we are committed to building a diverse and inclusive workforce so if you're excited about this role but your past experience doesn't perfectly align we'd still encourage you to apply.

Data Engineer London + 2 or 3 days work from home Circ £60,000 - £70,000 + Excellent Benefits Package A fantastic opportunity is available for a Data Engineer that enjoys working in a fast paced and collaborative team playing work environment. Our client has been expanding at a remarkable pace and have transformed their technical landscape with leading edge solutions. Having implemented a new MS Fabric based Data platform, the need is now to scale up and deliver data driven insights and strategies right across the business globally. The Data Engineer will be joining a close-knit team that is the hub of our client s global data & analytics operation. Previous experience with MS Fabric would be beneficial but is by no means essential. Interested candidates must have experience in a similar role with MS Azure Data Platforms, Synapse, Databricks or other Cloud platforms such as AWS, GCP, Snowflake etc. Key Responsibilities will include; Design, implement, and optimize end-to-end solutions using Fabric components: o Data Factory (pipelines, orchestration) o Data Engineering (Lakehouse, notebooks, Apache Spark) o Data Warehouse (SQL endpoints, schemas, MPP performance tuning) o Real-Time Analytics (KQL databases, event ingestion) o Manage and enhance OneLake architecture, delta lake tables, security policies, and data governance within Fabric. o Build scalable, reusable data assets and engineering patterns that support analytics, reporting, and machine learning workloads. Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver effective solutions. Troubleshoot and resolve data-related issues in a timely manner. Key Experience, Skills and Knowledge: Proven 2 yrs+ experience as a Data Engineer or similar role, with a strong focus on PySpark, SQL, Microsoft Azure Data platforms and Power BI an advantage Proficiency in development languages suitable for intermediate-level data engineers, such as: Python / PySpark: Widely used for data manipulation, analysis, and scripting. SQL: Essential for querying and managing relational databases. Understanding of D365 F&O Data Structures is highly desirable Strong problem-solving skills and attention to detail. Excellent communication and collaboration abilities. This is a hybrid role based in Central / West London with the flexibility to work from home 2 or 3 days per week. Salary will be dependent on experience and expected to be in the region of £60,000 - £70,000 + an attractive benefits package including bonus scheme. For further information, please send your CV to Wayne Young at Young's Employment Services Ltd. YES are operating as both a recruitment Agency and Recruitment Business

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III at JP Morgan Chase within the Corporate Risk Technology, you serve as a seasoned member of an Agile Engineering & Architectureteam to design and deliver trusted market leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. Job responsibilities Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Creates secure and high quality production code and maintains algorithms that run synchronously with appropriate systems Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture Contributes to software engineering communities of practice and events that explore new and emerging technologies Adds to team culture of diversity, opportunity, inclusion, and respect Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and applied experience. Proficiency in Data Engineering & Architecture, AI/ML with hands on experience in designing, implementing, testing, and ensuring the operational stability of large scale enterprise platforms and solutions Advanced in one or more programming language(s) eg. Java, Python , C/C++, C# Working knowledge of relational and NoSQL databases and data lake architectures Experience in developing, debugging, and maintaining code (preferably in a large corporate environment) with one or more modern programming languages and database querying languages with good overlap of application & DB. Experience in large scale data processing, using micro services, API design, Kafka, Redis, MemCached, Observability (Dynatrace , Splunk, Grafana or similar), Orchestration (Airflow, Temporal) Proficiency in automation and continuous delivery methods Proficient in all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Practical cloud native experience Preferred qualifications, capabilities, and skills Experience with modern data technologies such as Databricks or Snowflake. Hands on experience with Spark/PySpark and other big data processing technologies Knowledge of the financial services industry and their IT systems