Top Data Jobs in London

Lead BIM delivery for a major data centre project across design, construction, close-out and handover. Manage BIM mobilisation, execution planning, model quality, clash detection, CDE workflows, information standards, dashboards, stakeholder coordination and compliance. Oversee model reviews, issue resolution, asset data, site verification integration, as-built documentation and final digital deliverables while providing governance and assurance across designers, contractors, vendors and specialist teams.

Set technical direction for AI engineering and lead complex LLM-powered products from experimentation to production. Design reliable systems using RAG, vector search, tool calling, agentic workflows, and context management. Establish evaluation, monitoring, observability, security, safety, governance, and production safeguards. Influence architecture, model and vendor selection, and cross-team engineering strategy while mentoring teams through technical leadership.

Own production machine-learning models that detect prompt injection, data exfiltration, policy violations, and other AI threats. Train and deploy low-latency classifiers, analyze telemetry for drift and false positives, build evaluations and benchmarks, and convert new attacks into training data. The role also translates policies and regulations into measurable controls while improving model quality and latency. Candidates need substantial applied ML or data science experience, strong Python and PyTorch skills, NLP and LLM expertise, evaluation statistics, and clear communication.

Manage market data compliance activities, exchange and broker licensing, application onboarding, and external audits. Serve as a relationship contact for exchanges, brokers, internal stakeholders, and audit providers. Identify and mitigate compliance issues, communicate pricing and policy changes, and support cost efficiency, operational standards, and service improvements across proprietary applications.

Implement and assess data governance controls supporting financial crime analytics. Develop data dictionaries, lineage documentation, data quality dashboards and scorecards; resolve data quality issues; and recommend sustainable improvements. Partner with financial crime data and systems experts to strengthen reporting, decision-making and regulatory data management. The role requires experience with governance frameworks, Collibra, analytical tools, programming, and economic crime, fraud, AML, regulatory reporting or risk.

Leads governance, risk, compliance, audit, and assurance activities across complex cybersecurity programs. Evaluates policies, controls, evidence, risks, and framework compliance across IT and OT environments; performs gap and maturity assessments; develops defensible findings and remediation recommendations; validates corrective actions; and reports results to executives. Provides day-to-day leadership, quality review, stakeholder facilitation, and coordination across technical, operational, and governance teams.

Leads Cafeyn’s customer data and data science strategy, overseeing analytics, machine learning, AI-powered product innovation, experimentation, data monetization, governance, and scalable data foundations. Manages multidisciplinary data teams, partners with executive, product, marketing, business, and engineering stakeholders, and drives initiatives such as churn prediction, personalization, semantic search, KPI frameworks, and A/B testing to improve engagement, retention, revenue, and decision-making.

Leads cost and commercial management for major data centre construction projects, managing complex workstreams, client reporting, quality assurance, contract compliance, and service improvements. Supervises and develops cost specialists, supports project delivery, builds stakeholder relationships, and provides construction cost analysis and insights. The role requires substantial travel to Norway, potentially on a 50/50 rotation.

Oversee environmental, health, and safety performance for a major data centre construction project in Norway or Finland. Responsibilities include implementing EHS and security plans, verifying site procedures, holding managers and contractors accountable, monitoring performance indicators, investigating incidents, conducting audits and inspections, and ensuring corrective actions are completed. The role requires extensive EHS advisory experience on major construction projects and may involve significant travel on an 11/3 rotation.

Oversee mechanical construction quality across construction, commissioning, and handover phases for a major Finnish data centre project. Review ITPs, checklists, drawings, specifications, and BIM 360 records; verify workmanship, contractor compliance, equipment calibration, and as-built documentation. Identify and resolve quality issues, support commissioning of HVAC, pumps, piping, cooling, and fire protection systems, and sign off completed works before energisation. The role requires extensive construction quality experience, strong mechanical knowledge, and frequent Finland-based travel or rotation work.

Leads large-scale hyperscale data centre construction projects from pre-construction through closeout and fit-up. Responsibilities include managing schedules, budgets, contractors, vendors, procurement, contracts, HSE, quality control, commissioning, documentation, permits, and client relationships. The role coordinates multidisciplinary teams and Owner’s Representatives, supports commercial and contractual activities, and requires significant international travel to Nordic project sites.

Leads environmental, health, safety, and security strategy for a major Nordic data centre construction project. Responsibilities include governing the project EHS management system, overseeing contractors, reviewing RAMS, conducting audits and inspections, investigating incidents, ensuring emergency preparedness, monitoring performance metrics, and liaising with clients, executives, contractors, and regulators. The role requires senior leadership, strong construction or infrastructure experience, and preferably hyperscale data centre expertise.

Design and build data foundations using Python, SQL, NoSQL, graph databases, and knowledge graphs. Define ontologies, create ingestion and transformation pipelines, resolve entities, maintain provenance, design schemas, develop queries, enforce data validation, and manage model evolution, migrations, backfills, and recovery across heterogeneous data sources.

Own the reliability of production data services and processing workloads across secure customer environments. Build CI/CD and GitOps workflows, orchestration tooling, monitoring, alerting, recovery procedures, and operational automation. Troubleshoot Kubernetes, Linux, networking, storage, databases, and production incidents while improving runbooks and ensuring secure integration with identity, secrets, and network controls.

Own the vision, strategy, roadmap, development, launch, and adoption of AI and ML-powered data products. Partner with Data Science, ML Engineering, Design, Sales, Marketing, Finance, and clients to define product value, quality standards, responsible AI practices, commercial models, pricing, and packaging. Lead prioritization, communicate trade-offs to executives, and guide a cross-functional squad in a fast-changing environment.

Manages financial accounting, general ledger integrity, month-end and year-end close, balance sheet governance, controls, compliance, and reporting across international entities. Leads process standardization, automation, and finance transformation using Oracle Fusion, OneStream, Smart View, and Excel. Oversees audits and statutory requirements, resolves accounting issues, develops up to two direct reports, and partners with finance stakeholders to improve accuracy, efficiency, and scalability.

Design, build, and optimize Phantom’s streaming blockchain data platform, including scalable ETL pipelines, data models, schemas, quality frameworks, observability, and high-availability systems. The role delivers accurate, low-latency token, price, and spam data to engineering teams, collaborates cross-functionally, and contributes to team growth. Experience with backend systems, modern data engineering, and Web3 or on-chain data is expected.

Develops CRM segmentation, audience strategies, predictive models, and personalized marketing campaigns using Salesforce platforms and SQL. Maintains audience libraries, validates data pipelines, governs customer data, supports experimentation and performance measurement, and creates lookalike and suppression audiences. Collaborates with Data Engineering, Data Science, IT, and marketing teams to ensure data quality, privacy compliance, campaign accuracy, and operational efficiency. Mentors analysts and marketers while improving CRM processes and personalization capabilities.

Summer data and analytics intern supporting consulting engagements involving investigations, regulatory inquiries, disputes, and operational analysis. Responsibilities include collecting and analyzing large datasets, building data pipelines, applying AI and machine learning tools, creating visualizations, conducting quality control, and collaborating with clients and senior colleagues. The role provides experience across data engineering, cloud technologies, advanced analytics, and AI.

Summer interns support FTI Consulting’s Data, Technology and Transformation team by analyzing data, defining requirements, identifying business improvements, and delivering client-focused technical and business solutions. Responsibilities include data analysis, forecasting, stakeholder collaboration, problem solving, reporting, and contributing to transformation initiatives. Candidates receive coaching and professional development while working on projects across data services, technology strategy, process automation, finance transformation, and business intelligence.

Administer SKAN AI and ProHance platforms, develop Power BI dashboards and automated reporting, analyze operational and workforce data, and identify process improvement opportunities. The role supports process intelligence, productivity analysis, workflow automation, system integrations, business application development, and data-driven recommendations. Responsibilities also include stakeholder engagement, user training, documentation, governance, platform maintenance, and translating business requirements into scalable analytics and process optimization solutions.

Build and lead engineering for a Snowflake enterprise data platform supporting banking transformation. Responsibilities include platform foundations, access controls, infrastructure as code, CDC and heterogeneous data ingestion, metadata-driven frameworks, dbt transformations, canonical and dimensional modeling, data quality, governance, orchestration with Snowflake Tasks and Dynamic Tables, monitoring, and AI-ready data products. The role partners with architects and application teams, defines engineering standards, and may lead, mentor, recruit, and coordinate a data engineering team.

Develop data-driven insights, predictive models, optimization solutions, and simulation-based decision-support tools for semiconductor manufacturing. Analyze manufacturing and operational datasets, apply statistical and machine-learning techniques, design experiments, and improve planning, scheduling, resource utilization, and factory performance. Collaborate with customers, domain experts, and engineering teams, communicate findings to technical and non-technical audiences, and contribute to manufacturing intelligence research and innovation.

Lead definition, monitoring and reporting of Group financial crime KRIs and tolerances. Drive data quality, investigations and MI for AML, sanctions, fraud and CDD. Partner with technology and business units to maintain data infrastructure, implement automated reporting, enhance controls and deliver dashboards and governance across the organisation.

Provide technical leadership for ENSEK’s data ecosystem, owning data architecture, platform strategy, roadmap, and data mesh adoption. Establish standards for event-driven architecture, schema governance, data quality, observability, lineage, metadata, security, and cost management. Design governed data-sharing interfaces for customers and partners, solve complex engineering challenges, influence senior stakeholders, and mentor engineering teams.