Top Data Analyst Jobs in London

Leads data analysis, modelling, benchmarking, dashboard development, and performance reporting for large-scale infrastructure projects. Manages project controls data covering cost, schedule, risk, quality, and change; develops KPIs and earned value reporting; identifies trends and root causes; and provides intelligence to support investment and project decisions. The role also leads Data Analysts, manages stakeholders, and promotes continuous improvement and digital transformation.

Own Retail Media and ecommerce analytics, including Looker governance, GA4 performance analysis, metric definitions, reporting automation, and data-quality improvements. Collaborate with Analytics Engineering, Product, commercial stakeholders, and international retail partners to develop reporting marts and semantic layers. Present actionable insights, support technical analysis, and mentor junior analysts.

Conduct high-output analyses for customers, research teams, and senior analysts. Translate structured and unstructured data into defensible findings, recommendations, visualizations, and executive-ready narratives. Scope data needs, collaborate with data engineering and cross-functional teams, use SQL and analytical tools, and apply AI-assisted workflows while validating results. The role also involves maintaining accuracy, working across diverse business questions, and progressively identifying new insights for operations and supply chain leaders.

Generate actionable insights from complex customer, behavioral, lifecycle, and product data. Collaborate with product, commercial, CRM, content, and leadership teams to define analytical questions, test hypotheses, measure business impact, and support evidence-based decisions. Present clear data stories, challenge assumptions, promote data-driven decision-making, and automate recurring reporting and analysis.

Leads digital data and analytics roadmap delivery, data governance, taxonomy, measurement frameworks, dashboards, experimentation, and AI-enabled analytics. Partners with marketing, technology, and client experience stakeholders to translate business needs into trusted reporting, reusable data products, actionable insights, and Adobe Experience Platform requirements.

Embedded within the commercial team, the Staff Data Analyst will own trusted metrics for conversion, contracted volume, sales, margins, pipeline, and forecasting. Responsibilities include improving forecast accuracy, diagnosing CRM and transactional data quality issues, analyzing commercial opportunities and partner performance, identifying risks and trends, and translating complex findings into recommendations for senior stakeholders. The role also promotes metric adoption and self-service analytics across non-technical commercial teams.

Analyze Wise Platform pricing, costs, and profitability to identify pricing improvements and growth opportunities. Investigate complex cost data, improve data quality and allocation methodologies, explain product economics, monitor financial performance, and support pricing model enhancements. The role requires advanced SQL, visualization, dbt data modeling, stakeholder influence, and collaboration across analytics, engineering, and business teams.

Generate actionable growth and financial insights through dataset curation, metric development, statistical modeling, and deep-dive analysis. Analyze company and regional growth drivers, customer segments and cohorts, and the financial impact of marketing and product initiatives. Build data visualizations and communicate findings to influence business decisions, while managing stakeholders and organizing work independently.

Monitor product functionality, analyze and query data, build dashboards, provide management information, and support cross-functional decision-making. The role owns reporting processes, develops operational controls, investigates issues, and automates recurring analysis using SQL and Python. It also maintains coding and visualization standards, reviews other analysts’ SQL, and communicates data-driven insights to stakeholders across Finance, Operations, Product, and Engineering.

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 analytical projects from problem definition through delivery, developing dashboards, models, datasets, and AI-enabled solutions. Partner with stakeholders to translate requirements into actionable insights, communicate findings, improve data literacy, and influence organisational decision-making. Provide technical leadership, mentor colleagues, and promote innovation and continuous improvement across data and analytics workstreams.

Own analytics across the participant lifecycle to support acquisition, onboarding, activation, engagement, quality, retention and reactivation. Build metrics, dashboards, and experimentation frameworks with SQL and Python; partner with Product, Operations, Growth, and Data Science to run experiments and translate marketplace data into actionable decisions that improve participant health and supply sustainability.

Deliver training and communications that improve colleagues’ data literacy and adoption of data products. Create accessible content, facilitate demonstrations and champion communities, analyze user statistics to measure tool uptake, and support the Data Culture Manager with change projects. The role also collaborates with the Microsoft Power Platform team to automate processes and promote effective data-driven decision-making across the organization.

Analyze and model electricity grids across global markets, including power flows, grid constraints, interconnection queues, stability, and techno-economic optimization. Support grid investment plans, capex strategy, and non-wire solutions such as flexibility and battery energy storage. Develop data and modeling tools, generate insights from complex energy datasets, and communicate findings clearly to technical and non-technical stakeholders.

Owns revenue intelligence data models, governed datasets, LookML models, dashboards, and data quality processes. Integrates Salesforce and subscription billing data in BigQuery to report ARR, retention, churn, pipeline, and renewals. Partners with Sales, Customer Success, RevOps, Finance, and other stakeholders to define metrics, resolve data issues, and deliver trusted analytics. Applies software engineering practices to BI development and supports AI-assisted revenue analytics.

Owns end-to-end revenue and marketing data integration, including ETL pipelines, dbt modeling, data quality monitoring, and Metabase dashboards. Analyzes SaaS revenue and marketing metrics, explains performance changes, and builds forecasting and churn-risk models. Partners with Revenue and Marketing teams to deliver reliable metrics, actionable insights, and scalable reporting.

Owns content analytics end to end, including engagement measurement, event instrumentation, audience analysis, content classification, competitive coverage tracking, and editorial attribution. Builds dbt models in BigQuery or similar warehouses and maintains the Omni semantic layer for trusted self-service reporting. Partners with editors to diagnose performance drivers, prioritize coverage, and translate complex analysis into actionable editorial strategy.

As a Data Analyst, you will develop data solutions, conduct diagnostics and analysis for technical projects, and collaborate with clients to design effective outcomes.

Leads end-to-end business analysis for AI, automation, and data initiatives within the tax technology function. Responsibilities include stakeholder workshops, requirements gathering, process analysis, user stories, acceptance criteria, backlog refinement, traceability, dependency and risk management, solution alignment, and UAT planning and execution. The role bridges tax business stakeholders with product, architecture, delivery, and testing teams to ensure technology solutions meet agreed business needs.

Support the end-to-end analytics stack: respond to data requests, contribute to dbt models/tests/docs, build BI dashboards in Hex, automate regulatory reporting, operate and govern data tools, assist migrations and ad-hoc investigations, and drive data quality and governance across the business.

Leads CRM data strategy, governance, quality, compliance, integrations, reporting, and analytics. Acts as the Salesforce and CRM data subject matter expert, supports AI and predictive analytics initiatives, and delivers customer, marketing, and commercial insights. The role collaborates with business and technical stakeholders, manages external partners, and coaches a CRM Data Executive while driving data capability improvements and informed decision-making.

Work cross-functionally to design and execute data-driven strategies across pricing, promotions, forecasting, growth, credit risk, and product analytics. Build models and monitoring, evaluate new product/channel opportunities, present insights to leadership, validate deployed strategies, and mentor junior analysts to scale the business.

Lead analysis of operational data to support decision-making. Build dashboards and reports, partner with operations stakeholders to identify process improvements, monitor KPIs, and inform strategic initiatives.

As a Senior Data Analyst, you will gather and document business requirements, manage stakeholders, analyze complex datasets, and create data models and dashboards.

As Lead Data Analyst, you will monitor and ensure the accuracy of forecasting models, diagnose forecasting errors, and communicate findings to stakeholders for operational improvement.