Analytics Engineering Manager
Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Aug 13, 2026. Zopa scores A on the Alion truth index.
The Team
Analytics Engineering is a central team working across Zopa's products rather than being embedded within one product area. The team has grown significantly as demand for high-quality, consumable datasets has increased. It works closely with Analytics and Data Engineering and is building stronger partnerships across Product and Engineering. The team is friendly, supportive and highly autonomous, with an expectation of high-quality delivery at speed. As the team grows, this role will provide closer leadership and development while helping shape Analytics Engineering standards, tooling and ways of working as Zopa's data and AI capabilities evolve.
A Day In The Life:
Lead, coach and develop a high-performing Analytics Engineering team.
Provide regular feedback, development support and effective performance management.
Own prioritisation across incoming requests, strategic initiatives, team capacity and longer-term projects.
Establish and deliver an Analytics Engineering roadmap aligned with Product and business priorities.
Improve the quality, reliability and scalability of analytical data products.
Embed strong practices across data modelling, testing, observability, documentation and CI/CD.
Work across Product, Engineering, Analytics and business teams to ensure Analytics Engineering delivers 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.
About You:
You have experience leading Analytics Engineering, BI Engineering or Data Engineering teams.
You have previous individual-contributor experience in Analytics Engineering.
You have a track record of building and developing high-performing engineering teams.
You have strong SQL and data-modelling expertise and experience with modern transformation tools such as dbt.
You have experience working with cloud data platforms such as Snowflake, BigQuery or Databricks.
You have defined technical roadmaps and delivered measurable business outcomes.
You can build trust and influence both technical and business stakeholders.
You understand modern engineering practices including testing, observability, documentation and CI/CD.
You have sufficient technical depth to identify systemic problems and contribute credibly to solutions alongside senior technical colleagues.
You can provide effective leadership to a highly autonomous team without micromanaging.
Added Bonus:
Experience building semantic or metrics layers.
Experience applying AI to Analytics Engineering workflows or developing AI-ready data products.
Knowledge of orchestration and ingestion tools such as Airflow, Dagster or Fivetran.
Python experience for automation or data engineering tasks.
Experience working in regulated financial services or another highly data-driven organisation.
Snowflake experience, given its introduction at Zopa.