26 to 39 of 39 Data Lake Jobs in the Thames Valley

Databricks Tech Lead – Azure Data Engineering (Contract) We are looking for a highly technical, hands-on … Databricks Tech Lead to join a large-scale digital transformation programme within the Energy Trading space. This role will focus on building, optimising, and scaling a data lake on Azure with particular emphasis on streaming pipelines, Delta Live Tables (DLT), and cost-efficient architecture. Role: Designing and developing streaming and batch data pipelines in Databricks … including DLT). Managing structured streaming in continuous mode, ensuring low-latency data delivery. Collaborating with architects, consultants, and business stakeholders to build a unified Azure-based lakehouse. Troubleshooting and optimising performance bottlenecks in high-volume streaming systems. Applying best practices for cloud cost management and efficient Databricks resource usage. Integrating data from on-prem and More ❯

CD pipelines (Jenkins), version control (GitHub/GitLab/BitBucket), backend/frontend frameworks (Spring Boot, Angular, React), cloud and data platforms (Azure Databricks, Data Lake), monitoring, logging, and test automation tools to deliver high-quality, scalable, and secure software solutions. This is an excellent opportunity for someone to lead and shape the engineering and More ❯

This is a strategic, front-office-aligned architecture role shaping the evolution of a multi-billion-dollar investment management platform. You’ll operate at the intersection of technology, data, and business value—driving change across portfolio management, trading, risk, compliance, and client operations. The remit demands a commercially astute technologist who can influence senior stakeholders, challenge legacy thinking … risk, performance, and operations. Oversee the implementation and optimisation of SimCorp Dimension , embedding industry best practice, scalability, and alignment to business strategy. Define and execute a multi-year data and platform strategy positioning the organisation as a market leader in digital investment operations. Engage senior business sponsors and C-suite stakeholders , translating complex architecture into business outcomes and … total-cost-of-ownership advantages. Champion data-driven decisioning across investment management, using benchmarking and insights to accelerate adoption. Drive SaaS and cloud transformation , shaping roadmaps that unlock economies of scale and enable future AI/ML-driven capabilities. Mentor cross-functional teams on data architecture, cloud design principles, and front-office solution delivery. Represent the More ❯

these values are upheld only because of our people. Your role As a Confluent Consulting Engineer, you will be responsible for designing, developing, and maintaining scalable real-time data pipelines and integrations using Kafka and Confluent components. You will collaborate with data engineers, architects, and DevOps teams to deliver robust streaming solutions. Required: • Hands-on experience … with Apache Kafka (any distribution: open-source, Confluent, Cloudera, AWS MSK, etc.) • Strong proficiency in Java, Python, or Scala • Solid understanding of event-driven architecture and data streaming patterns • Experience deploying Kafka on cloud platforms such as AWS, GCP, or Azure • Familiarity with Docker, Kubernetes, and CI/CD pipelines • Excellent problem-solving and communication abilities Preferred: Candidates … Kafka Connect, Kafka Streams, KSQL, Schema Registry, REST Proxy, Confluent Control Center • Hands-on with Confluent Cloud services, including ksqlDB Cloud and Apache Flink • Familiarity with Stream Governance, Data Lineage, Stream Catalog, Audit Logs, RBAC • Confluent certifications (Developer, Administrator, or Flink Developer) • Experience with Confluent Platform, Confluent Cloud managed services, multi-cloud deployments, and Confluent for Kubernetes • Knowledge More ❯

Product Manager – Data & AI Innovation (Air Platform) Location: London (Hybrid) Salary: £100-120,000 + bonus Type: Full-time, Permanent About Our Client Our client is a global financial technology leader driving innovation across data, automation, and AI. Their solutions power some of the world’s largest financial institutions, enabling them to transform operational efficiency, accuracy … and performance. They are now seeking a strategic Product Manager with deep expertise in data-driven product development and AI integration to lead innovation across their flagship Air Platform — a next-generation solution focused on intelligent automation, orchestration, and data optimisation. This is an opportunity to sit at the heart of AI transformation — defining strategy, shaping … product direction, and delivering next-level user experiences powered by AI agents, LLMs, and emerging technologies. The Opportunity As Product Manager – Data & AI Innovation, you will drive the roadmap for advanced data orchestration and AI-enabled features. You’ll collaborate with data scientists, engineers, and go-to-market teams to ensure each innovation is More ❯

point-to-site and site-to-site for high secure VPN connectivity from end user’s device and Sizewell C various offices and sites. Configuration of Data Lake storage, ensuring security hardening. Compliance of backup and restoration. Integration of IAAS, PAAS and SAAS application with Microsoft Entra ID (AAD) for secure access through SAML SSO. Maintain the More ❯

onsite per week) Contract Type: Contract Duration: 6–12 months (possibility of extension) Start Date: ASAP Overview We are seeking an experienced Machine Learning Engineer to join our data science and AI engineering team on a contract basis in London. The ideal candidate will be responsible for designing, developing, and deploying machine learning models and scalable data … advanced analytics and intelligent automation initiatives. This role offers a hybrid work arrangement , combining flexibility with collaboration, and is ideal for a contractor who thrives in fast-paced, data-driven environments. Key Responsibilities Design, build, and deploy machine learning models and AI-driven solutions to address business challenges. Collaborate with data scientists to transition prototypes into … production-ready systems . Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment. Optimise model performance, scalability, and reliability using MLOps best practices. Work with large-scale structured and unstructured datasets for model training and validation. Implement model monitoring, versioning, and retraining processes to ensure continuous improvement. Collaborate cross-functionally with engineering More ❯

General Ledger system to Finance functions across their EMEA entities. The main focus will be in Finance Data & Processing Architecture including the roll out of Azure Databricks Lake House and Oracle Cloud platforms supplemented with process orchestration, workflow and microservices. This is a newly created highly visible role, on a greenfield programme. A brilliant opportunity! The following … skills/experience is required: Strong Delivery Manager/Project Manager background. Previously implemented a General Ledger system Good working knowledge of finance processes and associated data sets/taxonomies. Understanding of Data lakes, Data sourcing, accounting rules engines, reference data, is desirable. Understanding of accounting is desirable. Excellent communication skills. Salary More ❯

track record in leading architecture for large-scale transformation programmes (legacy to modern/cloud) with deep expertise in architectural patterns & governance frameworks (e.g., TOGAF, event-driven design, data-centric architecture). You must be a skilled communicator, able to convey complex concepts to both technical and non-technical audiences and strong leadership qualities: negotiation, influence, conflict resolution … portfolio & order management), operations, and distribution. Strong grasp of modern enterprise technology stacks : Cloud platforms (AWS, Azure, hybrid environments) Containerisation & orchestration (Kubernetes, microservices) API-first design & integration strategies Data platforms (data lakes, MDM, unified investment data hubs, analytics platforms Hands-on experience guiding systems development lifecycle from concept to deployment. Proactive, adaptable problem-solver … with a “can-do” mindset. Finbourne LUSID data hub, operations automation, digital client platforms would be highly advantageous. Domain Knowledge: (Nice to Have) Asset Management – Investments, Mutual Funds, Pensions, Public and Private Assets (Real Estate, loans, etc) Capital Markets – Equities, Debt Funds and Securities Understanding of Commercial and Investment Banking More ❯

infrastructure and cloud with an eye for architecture as their business is evolving at speed. You will also be comfortable working in a financial regulated environment, Summary: Cloud, data, platform and cybersecurity experience in end to end systems As a Hands-on Leader, you will balance IT strategy with roll-up-your-sleeves delivery in a lean, agile … that aligns with business outcomes, driving requirements and collaborating across all teams. IT vendor management, offshore 3rd party experience IT governance and controls Technical Expertise includes: Azure, Reporting Data lakes and data analytics tooling (Power BI or similar), SQL databases, GDPR, and bridging the technical-actuarial gap. Delivery Expertise includes: ability to execute end-to-end … projects, either in-house or from consultancy engagement, with strong stakeholder collaboration. Requirements: Strong technical credentials in Azure, data architecture, and reporting Proven end-to-end delivery experience, ideally in Financial Services or consultancy Ability to bridge the gap between technical teams and Actuaries Hands-on leadership style, able to operate autonomously and collaboratively Right cultural fit: innovative More ❯

strategic IT solutions to Finance functions across their EMEA entities. The main focus will be in Finance Data & Processing Architecture including the roll out of Azure Databricks Lake House and Oracle Cloud platforms supplemented with process orchestration, workflow and microservices. This is a newly created highly visible role. A brilliant opportunity! The following skills/experience is … required: Strong Delivery Manager/Project Manager background. Good working knowledge of finance processes and associated data sets/taxonomies. Detailed understanding of Oracle EBS and Oracle Cloud. Good understanding of Data lakes, Data sourcing, accounting rules engines, reference data. Previously worked in an Investment or Corporate Bank. Understanding of accounting is desirable. Excellent More ❯

make equipment, software, and systems that help to plan, deploy, certify, monitor, and optimize all kinds of networks - like those for mobile phones, service providers, large businesses, and data centers. And we are also at the forefront of optical security - we bend light to develop and deliver optical solutions that provide security to the world's currencies and … monitor AI workloads in containerized cloud environments (Docker, Kubernetes, AWS/GCP/Azure) Participate in code reviews, architecture discussions, and mentor junior engineers Collaborate cross-functionally with data science, product, and operations teams Champion responsible AI practices and safety mechanisms in all development work Pre-Requisites/Skills/Experience Requirements: Bachelor's degree in Computer Science … Anthropic) or ML frameworks (PyTorch, TensorFlow) Solid understanding of CI/CD, Git, testing, and agile methodologies Hands-on experience with Linux, Docker, and containerized deployments Familiarity with data engineering concepts (SQL, ETL, data lakes) Experience with orchestration frameworks like LangChain, LangGraph, or Semantic Kernel Cloud deployment experience (AWS, GCP, Azure) Work on high-impact AI More ❯

workflows. Ensure reliability, scalability, observability, and security of production systems and ML infrastructure. Automate deployment, orchestration, and environment management using modern DevOps tooling. Collaborate closely with software engineers, data scientists, and product teams to bring ML-powered features to production. Proactively detect, troubleshoot, and resolve infrastructure and model performance issues. Stay up to date with industry best practices … tools (Docker, Kubernetes). Solid understanding of CI/CD systems (e.g., GitHub Actions, GitLab CI, ArgoCD) and infrastructure-as-code tools (e.g., Terraform, Helm). Familiarity with data engineering concepts such as ETL pipelines, data lakes, and large-scale batch/stream processing. Ability to design scalable, secure, and observable systems in fast-moving environments. More ❯

custom fine-tuning approaches. Architect scalable, secure, and cost-effective GenAI systems leveraging cloud platforms (Azure, AWS, GCP). Define integration patterns with existing enterprise systems (ERP, CRM, data lakes, APIs). Technical Leadership Collaborate with data scientists, ML engineers, and software developers to implement GenAI models. Evaluate and select appropriate GenAI frameworks, libraries, and model … deployments, ensuring alignment with business goals and technical feasibility. Governance & Risk Management Establish best practices for prompt engineering, model safety, bias mitigation, and responsible AI. Ensure compliance with data privacy regulations (GDPR, HIPAA, etc.) and internal governance policies. Define monitoring and observability strategies for GenAI systems in production. Stakeholder Engagement Translate business requirements into technical specifications and solution More ❯