Top Data Jobs in London

Lead the implementation and continuous improvement of enterprise Data Loss Prevention capabilities. Configure and optimize Netskope, Microsoft Purview, Wiz, and Kiteworks; manage data discovery, classification, labelling, secure file sharing, and DLP alerts. Investigate incidents, produce audit reporting, maintain security standards, and partner with cybersecurity, legal, compliance, privacy, and technology teams. Support automation, vendor management, regulatory compliance, and broader data security improvements.

Lead presales engagement for FE fundinfo’s Data Mastering and Nexus platform, including tailored demonstrations, presentations, workshops, RFP/RFI responses, and discovery sessions. Partner with commercial, product, customer success, solution architecture, and delivery teams to support new business and upsell opportunities. Gather market intelligence, develop scalable sales materials, contribute to webinars and industry forums, and act as a thought leader in asset management data management.

Own the paid media data domain end to end, including ingestion, user-level modeling, data marts, semantic definitions, reverse ETL, reliability, alerting, and incident response. Lead and mentor data engineers, establish technical standards, shape the roadmap, collaborate with platform and business teams, and remain hands-on in SQL and Python. Build production pipelines using dbt, Dagster, cloud warehouses, and related tooling while supporting analytics, machine learning, and data science use cases.

Lead pricing analytics for Wise Platform by investigating cost data, improving data quality and allocation methodologies, monitoring financial performance, and identifying profitability and growth opportunities. The role requires building complex SQL data sources, developing reusable dbt models, explaining product economics, influencing pricing strategies, and partnering with analytics, engineering, and business teams.

Own data extraction and integration across warehouses, business systems, and APIs. Build decision-focused Power BI or Tableau dashboards, answer urgent business questions, automate manual reporting with Power Automate or Zapier, and provide meaningful data insights to Finance, Sales, Operations, and Marketing. The role offers greenfield ownership and requires strong SQL, analytical ability, and independent project management.

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.

Build and maintain batch and streaming data pipelines for a modern AWS sportsbook data platform. Develop medallion-aligned datasets using SQL, dbt, Spark, and related tools; support Kafka or Flink streaming; implement data quality checks, schemas, monitoring, and governance; and troubleshoot pipeline performance and costs. Collaborate with analytics, data science, machine learning, trading, risk, and personalization teams to deliver reliable, scalable data assets.

Own Gridsight’s enterprise sales expansion across GB and Ireland, managing the full sales cycle from account prioritization and consultative discovery through tenders, procurement, and contract closure. Build pipeline and forecasting processes from scratch, develop utility partner and channel relationships, and collaborate with technical, delivery, and regional leadership teams. The role targets regulated electricity distribution and system operators with complex, multi-year B2B software sales.

Lead the design, deployment, and operation of scalable data pipelines and cloud infrastructure for Kpler’s marine insurance initiative. Build containerized AWS services using Python, Docker, Kubernetes, Airflow, and Terraform; manage PostgreSQL and Kafka/Flink streaming systems; establish observability standards; provide technical direction; collaborate cross-functionally; and mentor engineers.

Designs, builds, and operates secure cloud-native integrations and data platforms connecting internal systems, third-party platforms, correspondent banks, and data consumers. Responsibilities include Java and Spring Boot development, AWS infrastructure, event-driven data flows, Terraform, CI/CD, observability, data quality, and production support. The role contributes to architecture decisions, translates stakeholder requirements into technical solutions, mentors engineers, and promotes AI-assisted development practices.

Build and maintain cloud-native integration solutions connecting internal and third-party systems. Develop Java and Spring Boot services on AWS, write production code and tests, manage Terraform infrastructure and CI/CD pipelines, support observability and data quality monitoring, and participate in design and code reviews. The role also involves stakeholder collaboration, proactive issue resolution, and routine use of AI coding assistants and LLM-supported development practices.

Lead data-driven digital transformation solutions for large capital construction projects. Responsibilities include understanding client problems, advising on best practices, directing technical teams, mentoring junior staff, developing Azure, Fabric, Power BI, and Python solutions, productizing client solutions, and improving internal data processes. The role requires strong communication, analytical thinking, construction or engineering experience, and the ability to translate complex concepts for varied audiences.

Lead Mattioli Woods’ Group-wide Data & AI strategy, roadmap, governance, architecture, analytics, automation, and responsible AI practices. Build data foundations and quality controls across an acquisitive, FCA-regulated organization; identify workflow improvements; deliver AI and analytics into production; and build a high-performing internal team supported by specialist partners. The role involves communicating investment cases and outcomes to the CIO and Executive Committee.

Manages compensation processes, pay ranges, job families, and annual compensation cycles. Maintains HR data accuracy, governance, privacy, and reporting processes while developing Power BI and Excel dashboards. Analyzes workforce trends, provides insights to senior stakeholders, supports HR technology and analytics implementation, and improves compensation and reporting workflows. The role also collaborates with HR teams, presents findings, and supports data training and process improvement.

Lead complex data analytics initiatives for top financial institutions, utilizing predictive modeling and creating dashboards. Support innovation in AI and machine learning.

Manage customer data migrations and onboarding from initial handoff through completion. Responsibilities include mapping, analyzing, transforming, and importing complex datasets; coordinating with customers, engineers, and internal stakeholders; maintaining accurate records; resolving issues; and improving the onboarding experience. The role requires extensive Excel and database work, customer communication, project coordination, and management of multiple migrations simultaneously.

Own investigations and data-driven solutions across search, supply, and commerce. Analyze complex datasets using SQL and Python, identify incident patterns and product opportunities, connect data sources, and support cross-functional customer experience initiatives. Mentor junior colleagues, guide problem-solving, balance competing priorities, and help convert recurring issues into lasting improvements. Marketplace or product analytics experience is beneficial but not essential.

Sets technical direction for data and AI capabilities, leads large-scale production solutions, establishes engineering standards and reusable frameworks, improves AI monitoring and evaluation, partners with senior stakeholders, mentors engineers, and supports responsible AI adoption across the organization.

Leads end-to-end solution architecture across complex client engagements, transformation programs, and strategic opportunities. Shapes solutions from discovery and pre-sales through design, delivery, governance, and transition to service. Develops secure, scalable, resilient, commercially viable architectures spanning cloud, infrastructure, applications, data, AI, cybersecurity, networking, integration, and DevOps. Advises senior stakeholders, manages architectural risks, supports bids and proposals, assures delivery, develops reusable patterns, and coaches other architects.

Leads Pure DC’s project management function across customer fit-outs, construction-to-operations handovers, lifecycle capital programmes, and internal projects. Owns customer relationships, budgets, contractor procurement, change management, commercial growth, risk, compliance, and delivery quality. Manages regional project teams and third-party partners across multiple geographies while establishing scalable governance, processes, and project controls.

Leads SCOR’s enterprise data platform ecosystem across Databricks and Palantir Foundry. Owns platform strategy, architecture, governance, security, compliance, FinOps, observability, modernization, and adoption. Builds a global platform Center of Excellence and leads engineers, architects, governance, and FinOps teams. Enables scalable data products, self-service analytics, AI workloads, and agentic AI innovation while aligning investments with business priorities and regulatory requirements.

Lead data architecture and cloud transformation engagements for financial services clients. Define enterprise data strategy, design scalable cloud-native data platforms, integrate governance, cataloguing, privacy and metadata capabilities, and present technical solutions to stakeholders while shaping Capco's data architecture offerings.

Lead and mentor data science teams to design, develop, and deploy ML and AI solutions (including GenAI/LLMs). Align technical outcomes with business goals, drive MLOps and model governance, and deliver scalable production systems.

Gridsight invites exceptional candidates in the United Kingdom to submit an expression of interest for future opportunities. The company develops SaaS solutions using data, machine learning, and AI to modernize electricity-grid operations, support renewable connections, and orchestrate distributed energy resources. Applicants should explain their achievements, impact, motivation, learning ability, and alignment with Gridsight’s low-ego, high-impact culture.

Build and launch scalable data pipelines, products, APIs, and tools for proprietary market research. Develop big data processing systems, reusable software components, AI-ready data assets, cloud infrastructure, and governance controls. Partner with investment professionals, researchers, data scientists, and Compliance to deliver reliable, auditable, compliant solutions while optimizing system performance, cost, and reliability.