Analytics Engineering Manager

Overview

As Head of Analytics Engineering, you lead and grow a high-performing analytics engineering team, shaping standards and roadmaps that align with product and business goals. You’ll elevate data quality, reliability, and scalability of analytic data products while embedding strong data practices across modelling, testing, observability, and CI/CD. You’ll partner with data, analytics, and product teams to deliver measurable value and drive adoption of emerging technologies, including AI-assisted development.

Pay / Benefits

• hybrid role with London office 2-3 days a week
• option to work from abroad up to 120 days a year
• flexible ways of working
• focus on work-life balance
• supportive, autonomous team culture

Responsibilities

• Lead, coach and develop the Analytics Engineering team
• Provide regular feedback and performance management
• Own prioritisation across incoming requests, strategic initiatives, and longer-term projects
• Establish and deliver an Analytics Engineering roadmap aligned with Product and business priorities
• Improve quality, reliability and scalability of analytical data products
• Embed practices across data modelling, testing, observability, documentation and CI/CD
• Collaborate with Product, Engineering, Analytics and business to deliver measurable value
• Partner with Data Engineering, Data Science and Analytics to contribute to a cohesive data platform
• Represent Analytics Engineering in wider engineering discussions and champion better data practices
• Drive continuous improvement, knowledge sharing and adoption of emerging technologies, including AI-assisted development

Key requirements

• Experience leading Analytics Engineering, BI Engineering or Data Engineering teams
• Previous individual-contributor experience in Analytics Engineering
• Track record of building and developing high-performing engineering teams
• Strong SQL and data-modelling expertise; experience with dbt
• Experience with cloud data platforms such as Snowflake, BigQuery or Databricks
• Defined technical roadmaps and delivered measurable business outcomes
• Ability to build trust and influence technical and business stakeholders
• Understanding of testing, observability, documentation and CI/CD
• Sufficient technical depth to identify systemic problems and contribute to solutions
• Ability to lead a highly autonomous team without micromanaging

• Leadership and people development
• Stakeholder management and influencing
• Communication and collaboration across cross-functional teams
• SQL
• Data modelling
• dbt

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