Top Analytics Engineer Jobs in London

Design, build, and maintain revenue data models and reconciliations across CRM, billing, and ERP. Deliver dashboards, forecasts, and analyses that explain revenue trends and support sales, finance, and executive decisions while improving data quality and integrity.

The Lead Analytics Engineer at Graphcore is responsible for developing and managing the analytics engineering layer, creating robust datasets and metrics, and collaborating with business stakeholders to enhance decision-making through reliable analytics.

As a Lead Analytics Engineer, you will mentor analysts, define data infrastructure, build core datasets, and promote best practices in data modelling and BI tools.

Lead Analytics Engineer to architect and scale Operations data in BigQuery, build robust ETL and data models for reporting, ML and LLM use, drive re-architecture of domains, set DW best practices, own data governance and testing, lead through others, and provide on-call pipeline support.

Design, own, and improve data models and ELT transformations (dbt/Snowflake) that support credit decisioning, pricing, portfolio analysis and investor reporting. Collaborate with analysts, engineers and stakeholders, lead triage of pipeline issues, mentor analysts, and improve efficiency, reliability and cost-effectiveness of the analytics transformation layer.

The Data Product Owner will design and manage analytics products, driving product delivery, optimizing architectures, and collaborating with stakeholders to meet business needs.

As a Senior Analytics Engineer, you will design models, optimize data pipelines, collaborate with teams, mentor juniors, and promote AI readiness.

As a Senior Analytics Engineer, you'll design and maintain data models, create dashboards, and ensure data quality, working closely with various stakeholders.

Design and maintain behavioural event models and Databricks pipelines to ensure high-quality, observable customer data. Own event schemas, data quality checks, semantic metrics, and instrumentation alignment to support analytics, experimentation, and self-serve reporting.

The Analytics Engineer will manage analytics engineering relationships, develop data models and tools, and apply software engineering practices to optimize data-driven decisions.

As an Analytics Engineer II, you will build and maintain analytical data models, collaborate on data pipelines, and contribute to key metrics and dashboards to support decision-making.

Lead design and evolution of core analytical data models, define analytics engineering standards, build and optimize ETL/ELT pipelines, own the BI/semantic layer (Looker/LookML), drive data quality and governance, partner with cross-functional teams, and mentor analytics engineering across the company to enable reliable, scalable decision-making and experimentation.

The Analytics Engineer will build and maintain data models using dbt, optimize SQL queries, and collaborate with teams to ensure data quality and performance.

Build, maintain and document tested, reusable datasets and data marts using dbt and cloud warehouses. Own daily operations, troubleshoot issues, perform code reviews, validate data, and collaborate with stakeholders to deliver analytics solutions and improve team practices.

The Analytics Engineer will deliver advanced analytics solutions, utilizing SQL and Python, support stakeholder needs, and enhance the data product within a hybrid work environment.

Lead the migration of reporting from SSRS to Snowflake, design scalable data models and semantic layers, build performant SQL transformations, introduce best practices (version control, CI/CD, testing), mentor BI developers, and collaborate with stakeholders to modernise reporting and governance.

As a Senior Analytics Engineer, you'll design AI-augmented workflows, build scalable data models, and enhance data governance practices, while collaborating with cross-functional teams.

The Senior Data Analytics Engineer will develop automated reporting solutions, analyze data across business functions, and enhance data quality. Collaboration with internal teams to drive self-service analytics and establish reporting standards is essential.

The Analytics Engineer will design and maintain Power BI dashboards, implement data models, and collaborate with stakeholders to ensure data solutions meet organizational objectives.

The Analytics Engineer will design and build Power BI solutions, define DAX measures, develop dashboards, and work with stakeholders to translate reporting needs into technical specifications. Requires extensive experience in Power BI and analytics engineering.

The Analytics Engineer will transform raw data into insights, manage the data stack, automate processes, and engage with stakeholders to optimize data usage.

The Lead Analytics Engineer will oversee data architecture for borrowing, develop robust data models, enhance data governance, and improve data practices to enable financial goals for customers.

The Senior Analytics Engineer will build and maintain data products and infrastructure, collaborate with teams, mentor other engineers, and enhance data-driven decision making across the organization.

Design and optimise downstream data models in BigQuery to support reporting, ML, financial and regulatory use cases. Build and maintain scalable ETL pipelines, define data modelling and testing standards, improve warehouse performance and data quality, collaborate cross-functionally, own pipelines and provide occasional on-call support.

Develop and enhance Neo4j Graph Analytics for Snowflake, focusing on SQL-facing APIs, build pipelines, and improving security while collaborating with clients.