Top Data Jobs in London

Provide senior advisory and technical guidance for a foundational enterprise data program in financial services. Govern data mart modeling, schema and semantic-layer decisions; establish data science, reproducibility, documentation and data quality standards; assess analytical readiness; sequence remediation; advise on AI governance; and upskill FP&A and data engineering teams.

Supports EMEA FP&A through budgeting, forecasting, headcount planning, financial modeling, variance analysis, and monthly reporting. Develops Power BI dashboards and maintains financial data frameworks for leasing and revenue forecasting. Partners with senior stakeholders, supports board and investor reporting, and drives process improvements through automation and AI-enabled finance solutions.

Build and lead a global reliability and technical assurance function for Vantage's data center fleet. Define fleetwide reliability baselines and risk models, perform technical inspections across electrical, mechanical, controls and commissioning, drive corrective actions and closed-loop learning, establish standards, executive reporting, and scale a central assurance team.

Design, build, and evolve production-grade trading platforms and data-serving services. Optimize performance, throughput, and efficiency at scale while improving reliability, testing, automation, code quality, and observability. Participate in production support rotations, troubleshoot incidents, and drive operational improvements across distributed data systems.

Build and own data foundations for multimodal agent research, including collection, curation, preprocessing, quality validation, versioning, storage, retrieval, and delivery into training pipelines. Collaborate with research scientists on dataset specifications, evaluation benchmarks, annotation workflows, synthetic data, and preference data. Improve pipeline reliability, testing, documentation, and engineering practices while identifying data bottlenecks affecting research velocity.

Owns the end-to-end architecture of IG’s GCP data platform, including BigQuery, Kafka ingestion, transformation, integration services, data quality, observability, and self-service patterns. Leads complex migrations from AWS and on-premises systems, establishes engineering standards, mentors data engineers, reviews designs and code, manages third-party delivery quality, and partners with cross-functional stakeholders in a regulated financial services environment.

Supports quality assurance and data integrity for financial reporting across complex asset portfolios. Responsibilities include asset evaluations, VIE assessments, provision notices, reconciliations, exposure reporting, borrower-rating monitoring, system updates, discrepancy investigations, documentation, and regulatory reporting. The role coordinates across front office, finance, and back-office teams, manages deadlines, supports QA checks, and guides junior colleagues.

Lead research and measurement strategies for major global advertisers, managing data requests, campaign ROI analysis, measurement solutions, client workshops, QBRs, thought leadership, and executive storytelling. Build consultative relationships with media, data, consumer insights, and brand stakeholders while collaborating across global account, sales, marketing, studio, and data teams. The role requires deep programmatic advertising knowledge, marketing mix modeling, attention measurement, cookieless media expertise, and proficiency in Excel and PowerPoint.

Own B2C marketing KPIs, reporting, acquisition funnel analysis, attribution, measurement studies, tracking, and self-serve data products. Use SQL and Python to generate actionable growth insights, improve marketing measurement, activate customer data, and develop AI-powered analytics solutions. Partner cross-functionally with Marketing, Product, and Data teams while ensuring tracking accuracy and regulatory compliance.

Coordinate group payroll processes across UK and rest-of-world, liaise with Global Mobility, P&C and outsourced providers, handle payroll queries and calculations, prepare journals for Oracle, update payroll procedures, and support meetings and implementation.

Build, ship, and maintain production data science models for attribution, marketing mix modelling, incrementality testing, and brand impact measurement. Independently select modelling approaches, debug code, collaborate with QA, communicate with clients as a modelling expert, use AI tooling and automation, and mentor junior colleagues.

Develop and maintain data science models for marketing measurement products, including attribution, forecasting, optimization, and experimentation. Own analytical investigations, model backtesting, production bug fixes, and pipeline work. Write and review Python and SQL production code, debug unfamiliar repositories, use AWS and QA tooling, and communicate findings to clients and colleagues. The role also involves applying machine learning methods, reviewing AI-assisted code, clarifying requirements, and progressively taking ownership of technical areas.

Own data science and analytics for the Shipping team, analyzing buyer and seller behavior, delivery performance, carrier economics, and product outcomes. Design and evaluate A/B tests, build dashboards and scalable datasets, debug data issues, and provide strategic recommendations. Partner with product, operations, engineering, platform, and machine learning teams to improve shipping strategy, experimentation, and data-driven decision-making.

Own and optimise the support queue and operational health of the data management platform. Investigate and resolve complex data pipeline and quality issues, lead client onboarding/configuration, coordinate cross-functional stakeholders, drive incident prevention and platform reliability, and mentor junior team members while ensuring data governance and secure user access.

This role involves building and operating a data platform, delivering reliable data products, and improving engineering workflows with AI and automation while mentoring junior team members.

Lead mechanical delivery for hyperscale and co-location data centre projects across UK/EMEA. Drive technical excellence, client relationships, work-winning, team leadership, and project financial management for mission-critical environments.

Lead mechanical delivery for hyperscale and co-location data centre projects across EMEA. Act as sector ambassador, drive technical excellence, win work, manage project financials, lead teams, and ensure high-quality mechanical design and client engagement for mission-critical environments.

Lead electrical design and engineering for data centre projects, ensuring performance and energy efficiency while managing multidisciplinary teams and building client relationships.

Lead design and engineering for data centre projects, ensuring optimal performance. Manage teams, engage with clients, and mentor junior engineers.

The Principal Mechanical Engineer will lead mechanical engineering projects for data centres, managing multidisciplinary teams and contributing to strategic growth and thought leadership.

Senior consulting leader who owns the strategic value narrative and client relationships across data platforms, AI and end-to-end software engagements. Leads discovery, executive workshops, alignment, change management and adoption, supervises delivery leads, supports pre-sales, and grows client engagements through solution shaping and go-to-market propositions.

Lead enterprise data product strategy, governance, lifecycle and adoption. Orchestrate cross-domain prioritization, manage dependencies, own roadmap and demand intake, and engage senior stakeholders to drive value and alignment across Data, IT, and business domains.

Define and evolve end-to-end data architecture for real-time news ingestion, enrichment, storage, indexing, and distribution. Develop data standards, schemas, and contracts; normalize metadata for discoverability; ensure observability and lineage; influence platform strategy; collaborate with engineering and product leaders; pragmatically evaluate tools to improve reliability and performance.

Consult as a data scientist to design, build and deliver advanced analytics and ML solutions across the full modelling lifecycle. Translate client needs into analytical approaches, perform exploratory analysis, develop and test models, and handover solutions using tools like Python, SQL, Databricks and visualization platforms.

Join an R&D team building a high-performance data warehouse. Design, develop, and test data warehouse microservices; troubleshoot field issues; collaborate with Product and Technical Support to prioritize and assist customers. Work across the stack on performance, cluster management, security, and debugging.