Top Data Jobs in London

Accountable for enterprise-wide data governance, risk and management. Own policy, standards, oversight and reporting; drive remediation, cross-business alignment, governance forums and continuous improvement to maintain data risk within appetite.

As a Senior Data Scientist, you will lead forecasting model development for various logistics domains, ensuring operational efficiency and cost reduction by integrating models with business needs and addressing performance issues.

The role involves designing scalable data pipelines for 3D, video, and sensor data, optimizing infrastructure, and productionizing ML models with researchers.

Lead canonical data modelling and governance for buy-side data domains, translating logical models into Snowflake-ready schemas, DDL, API contracts and data quality rules. Work with investment, operations and ESG teams to define lineage, golden sources, industry-standard mappings (ISO20022, SWIFT, FINOS CDM), and embed governance while mentoring engineers to ensure implementation fidelity.

Lead privacy governance and compliance across EMEA & UK. Advise business units on data protection, maintain knowledge of regional laws, develop policies and training, support privacy risk monitoring, eDiscovery and incident remediation, and coordinate privacy requirements for new technologies.

Support end-to-end processing of delegated bordereaux data (risk, premium, claims): validate, reconcile, monitor receipt, manage queries with third parties, contribute to MI/reporting, and drive process standardisation and continuous improvement to reduce manual work.

The Senior Data Scientist will develop predictive models, conduct statistical analysis, and work with cricket datasets to uncover trends and validate model performance.

Lead delivery of ground-up data centre construction projects across Europe from inception to commissioning. Set success criteria and governance, manage planning, procurement, quality, safety, cost control, change management, reporting, client and consultant liaison, and lead cross-functional project teams to meet time, cost, technical and performance objectives.

Lead delivery of large-scale, ground-up data centre construction projects from inception through commissioning. Provide strategic advice at conception, set success criteria, establish governance and project controls, manage quality, safety and finances, oversee procurement and cross-functional teams, apply performance metrics and change control, and act as primary client interface throughout project lifecycle.

Lead end-to-end delivery of large-scale ground-up data centre construction projects: define success criteria, manage planning, procurement, governance, quality, safety, cost, change control, reporting, and client/consultant interfaces through commissioning.

Lead delivery of complex data centre real estate programmes and portfolios, ensuring projects meet time, cost and quality targets. Build client and stakeholder relationships, support bids and business development, improve programme management practices, and promote digital tools to enhance delivery and performance.

Build and maintain the data foundation (pipelines, warehouse) and develop AI-native agents and internal workflows on top of it. Enable product and cross-functional teams to make faster, data-driven decisions. Measure success by improving organizational speed and intelligence.

Handle complex, custom client requests by building end-to-end reports, performing quantitative analysis and data mining using SQL/pySpark and Python, developing research tools on Similarweb raw data, and partnering with Engineering and Advisory teams to scale solutions and deliver strategic data products.

The role involves designing and building backend services, UI components, and integrations, while maintaining solid infrastructure practices and contributing to team collaboration.

The job involves designing, developing and testing data warehouse microservices, troubleshooting field issues, and collaborating with product and support teams.

Lead cross-functional engineering teams to design, deliver, and evolve cloud-native, event-driven insurance applications. Own architecture, roadmap, and delivery for policy, claims, underwriting, and compliance systems while ensuring regulatory adherence, vendor management, Agile/DevSecOps practices, and engineering KPIs.

The Data Product Specialist develops analytics-ready data products, collaborates with teams to define specifications, supports data processes, and advocates for data product usability.

As an Associate Director, you will lead HV substation design for data centres, manage technical discussions, ensure quality delivery, and mentor junior engineers.

This role involves building and maintaining a global data warehouse and automated reports while supporting campaign reporting and improving existing data solutions.

Develop and enhance low latency market data systems using high-performance C++ in a collaborative team environment, contributing to architecture and project leadership.

As a Software Engineer in Data and Lifecycle, you'll design and implement solutions for trade automations, maintain reference data, and collaborate with stakeholders.

Seeking a Software Engineer for the Data and Lifecycle team to automate trade processes, maintain reference data, and collaborate with stakeholders on derivatives.

The Principal Product Manager for Data Platform will own the vision and roadmap for an AI-enhanced data discoverability platform, ensuring data assets are searchable and reusable. Responsibilities include defining platform capabilities, driving governance frameworks, and leading cross-functional collaborations to enhance data quality and user satisfaction.

The Data Centre Engineer will manage data centre operations including design, installation, and maintenance of equipment while ensuring data safety and accessibility.

The role involves managing data quality for portfolio risk analytics, troubleshooting data issues, and collaborating with teams to enhance data processes. It requires strong analytical skills and experience in financial data, risk models, and technical proficiency in relevant programming languages.