Top Data Jobs in London

Design, develop, and maintain data pipelines using Kafka; build infrastructure with Terraform; troubleshoot data engineering issues and collaborate with teams.

Drive go-to-market execution and growth for Support Services across regions. Lead lifecycle management from land to expand, align sales, services and partners, standardize offerings and operating models, track performance, mentor specialist communities, and support client engagement to increase adoption and long-term value.

Design, build, and deploy production-ready ML models emphasizing recommendation and ranking systems. Apply NLP and behavioural analytics to large-scale datasets using Databricks and Spark. Run experiments (A/B tests), monitor and optimise live models, and collaborate with engineers and product teams to deliver measurable business impact.

Lead and mentor a Data Engineering team to design, build, and optimize scalable Microsoft-based data platforms (Fabric, Databricks, Synapse, Azure). Develop PySpark/Spark SQL pipelines, orchestrate with ADF/Synapse/Fabric Pipelines, manage Azure DevOps and CI/CD, scope tasks, review code, and drive Agile delivery while acting as technical SME and stakeholder partner.

Lead global workforce planning and people analytics, building supply/demand models, scenario planning, dashboards, and predictive models. Partner with HR, Finance and segment leaders to align headcount, support restructuring and cost optimisation, ensure data governance and compliance, and present executive-ready workforce insights.

As a Data Analyst at GoHenry, you will analyze data, present insights, and collaborate with teams to drive product enhancements. Responsibilities include A/B testing, building robust dashboards, and continuous improvement of data practices.

Own end-to-end onboarding and normalization of external data into a standardized schema. Map client trade, market, and reference feeds to load-ready formats, coordinate with vendors and R&D, validate ingestions, maintain mappings, monitor feed health, and resolve schema gaps before production.

Lead COG Claims data strategy and delivery, building scalable data products, pipelines, and AI-ready assets. Partner with Claims Transformation and stakeholders to enable analytics, automation, RAG/AI Search, and enterprise ontologies. Manage Agile product teams, roadmaps, governance, and data quality to drive measurable business outcomes across global Claims.

Lead Nothing's data function from scratch: map priority use cases, design and build end-to-end pipelines connecting ERP, HRIS, app telemetry and trackers, own architecture and tooling choices, define data quality standards, and enable AI/LLM workflows to power business decisions.

Lead and deliver high-impact AI projects for life-sciences clients: define data science approaches, design robust software architectures, mentor junior data scientists, manage project delivery, build client relationships, and contribute to thought leadership.

Evaluate and onboard cross-asset market data feeds, maintain and enrich reference databases, improve data QA, liaise with vendors, produce analytics and reporting, support product development and client requests across TCA, venue analytics and trade surveillance.

Lead advanced statistical and machine learning analyses to generate actionable business insights; partner with cross-functional teams to design data-driven solutions; manage large datasets with strong governance; develop and maintain predictive models to forecast trends; communicate findings to stakeholders and stay current on industry technologies.

Develop and deploy credit risk and behavioural models for US unsecured loans and credit cards using machine learning. Translate business problems into data questions, run experiments, implement models, monitor performance, and communicate results to stakeholders.

Design, build, and maintain scalable data infrastructure and pipelines to support BI/MI workloads. Manage ETL/ELT processes, optimize performance and availability, resolve data quality issues, enforce security and governance, conduct code reviews, mentor engineers, and collaborate with product, data science, platform, and business teams.

Lead data architecture and strategy across OLTP, OLAP, and AI systems. Drive AI-first foundations (LLM orchestration, RAG, real-time inference), ensure DataOps/CI-CD, mentor technical leads, run architectural reviews, partner with product and engineering leadership, and optimise platform security, observability and costs.

As a Data Engineer, you will design, build, and maintain data pipelines and infrastructure to support data-driven decision-making in a collaborative environment.

Develop, fine-tune, evaluate, and productionise ML and LLM models for customer feedback tasks (extraction, retrieval, reranking, summarisation, sentiment). Build retrieval and embedding pipelines, contribute to evaluation frameworks and metrics, write tested code, collaborate on integrations and monitoring, and translate product needs into ML experiments while keeping up with research.

As an Energy Consultant, you'll bridge Gorilla's SaaS solutions with energy market needs, drive pre-sales engagements, and support deal strategies through workshops and tailored presentations.

Lead the Finance & Regulatory Data team, overseeing finance data strategy, governance, and analytics to support corporate finance and audits.

Use SQL and Python to analyse transaction monitoring and fraud rule performance, identify patterns and anomalies, reduce false positives, and prioritise high-risk cases. Partner with FinCrime, Product, Compliance and Data teams to improve controls, data pipelines and detection logic, support scoring and future ML use cases, and translate analysis into actionable recommendations that balance fraud prevention with customer friction.

The Data Mentor provides technical support and feedback to apprentices, ensuring high standards in teaching, learning, assessment, and learner progression monitoring.

As the Data Engineering Manager, you'll lead a team, manage data infrastructure, design scalable solutions, and drive data quality initiatives while collaborating with cross-functional teams.

The Senior Software Engineer II will design and implement generative AI services, drive architectural standards, mentor engineers, and collaborate across teams to enhance data solutions.

The Director Analyst focuses on data integration and engineering, providing insights, advice, and research to help organizations improve their data practices and strategies.

The Engineering Manager will lead cross-functional teams of engineers, focusing on building high-performing environments, managing technical delivery, fostering team growth, and ensuring data-driven strategies.