Top Data & Analytics Jobs in London

Own and productionise growth marketing analytics infrastructure: build scalable growth narratives, automate marketing financials and insights, develop Lightdash/Streamlit/AI tools, create payback and financial models, partner with Finance and Marketing, ensure data quality, and reduce technical debt by building reusable data components.

Design and deliver a real-time liquidity observability stack and core treasury functions. Build scalable, event-driven systems, implement monitoring and control mechanisms, automate cash investment and risk tooling, and collaborate with product, data scientists and stakeholders to forecast cash flows and optimize liquidity.

Lead end-to-end growth and marketing analytics: run deep-dive analyses, build dashboards and analytical frameworks, measure regional performance, and translate insights into actionable recommendations. Partner with senior regional marketing and product stakeholders, use SQL, Python, AI, and automation to build scalable analytical assets and support execution of growth initiatives.

Lead Analytics Engineer mentors analysts, defines data infrastructure roadmap, builds and maintains core datasets and analytics pipelines, drives adoption of tooling (dbt, Airflow, BI), and enforces data modelling, monitoring, testing, and best practices.

Lead product analytics for LATAM & MEA expansion: define and monitor KPIs, support product launches with forecasting and experimentation, build reusable data assets, and influence product decisions through clear data-driven insights and stakeholder storytelling.

Build and optimize Lakehouse data pipelines (Trino + Iceberg) using Medallion Architecture to transform high-throughput event logs into audit-ready subledgers and reporting metrics. Implement stream processing with Kafka, embed automated reconciliation/data quality checks, collaborate with finance and product stakeholders, and mentor junior engineers.

Lead product analytics for Wise Business: define and track KPIs/OKRs, build data logging and automated pipelines, run deep-dive analyses, quantify feature impact for prioritization, and translate findings into clear recommendations for product and leadership.

Lead development of the technical infrastructure to explain marketing growth drivers, automate insight generation, and productionise analytics tools (Lightdash, Streamlit, AI agents). Partner with marketing, regional, product, and analytics teams to identify opportunities, ensure data quality, and translate complex performance data into actionable strategies that drive execution and measurable impact.

Own end-to-end regulatory reporting datasets: map regulations to internal data, build and automate pipelines, implement data quality controls, create clear visualisations, investigate discrepancies, and partner with cross-functional stakeholders to ensure accurate, auditable reporting.

Lead analytics for FinCrime operations: own forecasting and capacity planning, maintain data pipelines, build predictive and causal models, assess operational health and costs, implement KPI frameworks, track initiative performance, and standardise processes across forecasting, scheduling, and real-time operations.