Top Data Jobs in London

Grow UK DSP revenue by selling digital out-of-home advertising solutions to brands, media agencies, and programmatic buyers. Responsibilities include prospecting, pipeline development, client relationship management, platform adoption, solution sales, training stakeholders on OOH trading and metrics, closing contracts, and representing the company at industry events. The role requires digital advertising technology knowledge, programmatic trading experience, business development ability, and confidence presenting technical and commercial solutions.

Design, build, and optimize scalable data pipelines and processing systems for sensitive clinical and genomic data. Develop AWS-based data solutions, models, storage, orchestration, quality controls, testing, automation, and observability. Support secure data acquisition, transformation, lineage, metadata, de-identification, and delivery while collaborating with engineering and specialist teams. Enable research, machine learning, and visualization through reliable data products and contribute to organization-wide data engineering practices.

Build and improve Enfuce’s people-data foundation by cleaning, structuring, connecting, and governing data across systems. Develop trusted BI reporting, analyze engagement, retention, workforce efficiency, and headcount trends, and provide actionable recommendations. Define success measures and evaluate people initiatives. Partner with the People, Data & AI, Finance, and People Product teams to support AI-powered automations and products using reliable data.

Senior leader responsible for strategic client portfolios, MMM and marketing effectiveness delivery, commercial growth, new business, and scientific quality. The role advises executive clients on budget optimization, forecasting, experimentation, and AI-powered measurement while managing profitability and resources. It also involves recruiting, coaching, succession planning, thought leadership, and shaping Ekimetrics’ UK business strategy.

Build and operate AWS-based data pipelines, datasets, and analytics applications for business stakeholders. Integrate and validate internal and external data, develop BI views, maintain infrastructure through code and CI/CD, and contribute to LLM-powered projects. The role also involves documenting systems, using agentic coding tools, and translating ambiguous business questions into reliable data products and insights.

Design and govern scalable cloud data architecture, pipelines, models, and migration strategies, including moving legacy solutions to Snowflake. Partner with engineering, analytics, data science, and business teams to support Power BI, machine learning, data governance, security, GDPR compliance, and strategic platform development.

Lead design and implementation of a business-critical data platform. Collaborate with stakeholders to define problems, propose technical solutions, own delivery to production, identify reliability issues, deliver architectural improvements, and influence the roadmap to ensure technical excellence in software and data engineering.

Lead high-impact AI projects, define data science approaches, design software architectures, mentor data scientists, shape client engagements, assess technical feasibility, and ensure rigorous delivery. The role requires advanced Python and machine learning expertise, leadership, commercial awareness, client-facing communication, and the ability to develop innovative algorithms across supervised learning, unsupervised learning, NLP, and validation.

Lead high-impact data science and AI projects for government and public-sector clients. Define data science approaches, design robust software architectures, lead project teams, mentor data scientists, assess technical feasibility, support client relationships, and ensure rigorous delivery. The role also involves thought leadership through courses, public speaking, or open-source contributions.

Conduct adversarial research against anti-bot and web fingerprinting systems, reverse engineer defenses, build and improve HTTP client solutions and machine-learning data collection methods to scale Bright Data's web data collection platform.

Design, deploy, and operate highly available database infrastructure across multi-cloud, virtualized, and Kubernetes environments. Migrate database services from virtual machines to Kubernetes, support disaster recovery and backup strategies, tune performance, and implement observability, logging, and alerting. Collaborate with engineering teams to resolve infrastructure challenges and automate workflows using scripting and infrastructure orchestration tools.

Designs and develops secure, scalable agentic commerce solutions for payments. Responsibilities include building agent orchestration components and MCP servers, developing Python services, creating Databricks data pipelines, supporting MLOps workflows, evaluating agent behavior, implementing observability, and improving operational stability. The role requires cloud-native engineering, API and event-driven services, LLM application development, responsible AI practices, Kubernetes, and secure production software delivery.

Leads the transition of Data Operations from manual processes to automated, workflow-driven operations. Responsibilities include clearing reference data backlogs, supporting ETRM trade operations, reconciling master and reference data, investigating issues with SQL, defining requirements and controls, maintaining EBX and ServiceNow workflows, managing trade failures, establishing runbooks and SLAs, and using operational KPIs to drive root-cause remediation and transformation priorities.

Lead UK data centre development from site origination through Ready-to-Build, including feasibility, land acquisition, grid connections, power solutions, planning, consenting, M&A, financing, procurement, and customer engagement. Manage relationships with landowners, authorities, advisors, investors, lenders, tenants, hyperscalers, and colocation operators. Coordinate technical, commercial, and development activities before handing fully de-risked projects to the EPC team.

Lead business intelligence and data analysis across railway programs, developing governed Power BI environments, semantic models, dashboards, and self-service analytics. Translate complex data into actionable insights, support decision-making and performance improvement, and drive analytics transformation and automation. Champion Power BI adoption through training and best practices while managing two analysts and a contractor. Engage senior stakeholders, industry partners, and suppliers to deliver trusted analytical products and recommendations.

Owns the end-to-end delivery and growth of non-documentary identity verification products, including QES, AES, and other electronic signing methods. The role manages product strategy, client adoption, partner relationships, analytics-driven optimization, documentation, support, fallback planning, and cross-functional delivery with engineering and global stakeholders.

Leads global clinical data transparency and regulatory disclosure activities across clinical registries, regulatory platforms, and freedom-of-information requests. Oversees therapeutic-area disclosure processes, anonymization and redaction, vendor relationships, budgets, compliance reporting, SOPs, audits, regulatory intelligence, and cross-functional initiatives. Advises stakeholders on evolving transparency requirements and represents the company in industry forums.

The Enterprise Solutions Manager drives operational excellence and client success through strategic analysis, process optimization, and project management, collaborating with various teams to deliver AI solutions.

Drives enterprise client success and operational excellence by scoping requirements, designing scalable processes, coordinating cross-functional delivery, analyzing performance, optimizing quality, and supporting analytics initiatives. Acts as a bridge between enterprise clients, a global talent network, and internal product, engineering, and operations teams. The role also includes mentoring operational staff, managing stakeholder relationships, and helping build new marketplace capabilities.

Leads the global Data & Analytics function, owning the Azure-based data platform, architecture, governance, security, data management, service delivery, budgets, vendors, and team leadership. The role establishes data quality, metadata, master data, access controls, and integration standards while partnering with corporate and operational stakeholders across global sites. It also oversees managed services, DevOps practices, audits, platform resilience, and analytics and AI/ML capability strategy.

Own go-to-market strategy and new-logo acquisition for Salesforce’s MuleSoft and Informatica data integration solutions. Engage CIOs, CTOs, and data executives, manage complex $100K–$500K ACV sales cycles, lead cross-functional solution teams, map territories, analyze whitespace, build pipeline, and provide quarterly forecasts. The role requires enterprise software sales expertise, quota achievement, new business development, and the ability to explain data integration and architecture concepts through executive-level business outcomes.

Own enterprise go-to-market strategy, new-logo acquisition, and greenfield expansion for Salesforce Data Foundation solutions, including MuleSoft and Informatica. Engage CIOs, CTOs, and Chief Data Officers, lead complex six- and seven-figure sales cycles, coordinate solution architects and services teams, manage territory planning, analyze whitespace, maintain pipeline, and provide accurate forecasts. Success is measured through contract value achievement, pipeline growth, forecast precision, strategic account penetration, executive satisfaction, and collaboration.

Lead Markel UK’s newly created Data, MI, Governance and Oversight function. Develop data and reporting strategy, establish trusted executive performance insights, strengthen governance and customer outcome monitoring, and support conduct risk oversight. Lead a multidisciplinary team while partnering with Operations, Finance, Risk, Compliance, Underwriting and Technology. Translate complex insurance, financial and operational data into clear recommendations that improve strategic decision-making and business performance.

Leads complex analytics engineering workstreams and builds scalable data models and solutions using SQL, dbt, Python, and modern data platforms. Drives data quality, testing, CI/CD, documentation, performance, and operational excellence. Partners with cross-functional teams to deliver trusted data products, reporting, and commercial insights. Owns data incidents, mentors engineers, influences technical strategy, and establishes engineering standards across the organization.

Build and productionize machine learning and AI systems, including model packaging, deployment, lifecycle automation, monitoring, batch and real-time workloads, and LLM capabilities. Contribute to internal ML platforms, CI/CD, testing, governance, observability, and responsible AI practices. Collaborate with data scientists, engineers, and product teams to deliver scalable, reliable ML features and shared tools.