Analytics Engineering Manager
Function: Data & AI Solutions
Location: Hybrid, London or Peterborough office
Curious about what’s next?
So are we. Join Compare the Market and help to make financial decision making a breeze for millions.
We’ve carved a meerkat-shaped niche and we’re looking for ambitious, curious thinkers who thrive in a fast-moving, high-impact environment. If you love accountability, embrace challenge, and want to make a real difference, you’ll fit right in.
We’d love you to be part of our journey.
As the Analytics Engineering Manager, you will lead and grow a team of Analytics Engineers responsible for building scalable, trusted and reusable data foundations that power analytics, decision making and AI across Compare the Market. You’ll lead the execution of the Analytics Engineering strategy by translating organisational priorities into high quality data products, trusted semantic foundations and modern analytics capabilities. Create the conditions for technical excellence, delivery outcomes and capability growth across the team.
You will partner with Staff Engineers, Platform teams, Data Scientists, Product teams and Data Leaders to evolve the technical direction, engineering standards and platform capabilities that underpin a modern self-service and AI-enabled data ecosystem.
Some of the great things you'll be doing:
- Lead and support a team of Analytics Engineers, fostering a high performing, collaborative and inclusive team culture.
- Accountable for performance management, career developmentengagement, retention, coaching and mentoring, ensuring engineers have clear growth pathways and opportunities to reach their potential.
- Build strong cross-functional relationships and work collaboratively with Product, Analytics, Technology, Platform and Data teams to identify priorities and deliver analytics engineering initiatives.
- Drive the design, evolution and stewardship of scalable, maintainable and analytics-ready data models, transformation pipelines and reusable data products using modern analytics engineering practices.
- Own the development and governance of trusted semantic foundations, ensuring consistent definitions of business metrics, entities and dimensions across analytics, reporting, self-service and AI use cases.
- Establish and maintain data contracts, lineage standards and governance controls that improve trust, traceability and change management across the data estate.
- Hold the team accountable for delivering high quality outcomes, meeting engineering standards and achieving agreed business objectives.
- Establish and uplift engineering standards across testing, documentation, CI/CD, observability and data quality.
- Define and implement data observability practices including monitoring, alerting and operational controls that improve reliability and consumer confidence in data products.
- Improve operational excellence across the analytics estate by reducing technical debt, streamlining workflows and improving developer experience.
- Lead delivery planning and execution across multiple initiatives, ensuring outcomes remain aligned to business priorities while balancing platform sustainability, innovation and delivery commitments.
- Drive adoption of self-service analytics capabilities by improving the accessibility, reliability and usability of trusted data products.
- Partner with Data Scientists and AI teams to ensure data products, semantic assets and model inputs are reliable, governed and fit for purpose for machine learning and AI-enabled solutions.
- Influence stakeholders at all levels across Product, Analytics, Technology and Data functions to align priorities, communicate trade-offs and manage delivery risks.
- Foster a culture of continuous improvement, psychological safety, accountability and knowledge sharing.
What we'd like to see from you:
- Experience leading Analytics Engineering, Data Engineering or Business Intelligence Engineering teams within a modern data environment.
- Advanced SQL skills and hands-on experience with dbt and modern analytics engineering practices.
- Proven experience designing and maintaining scalable data models, transformation pipelines and reusable data products.
- Experience establishing data quality, observability, lineage and governance practices within production environments.
- Experience designing or governing semantic layers, trusted metrics and reusable business definitions.
- Strong understanding of cloud-based data platforms and modern analytics ecosystems.
- Experience balancing technical strategy, platform improvement and delivery priorities across multiple stakeholders.
- Strong communication and influencing skills, with the ability to translate technical concepts for both technical and non-technical audiences.
- Proven people leadership capability including coaching, performance management and talent development.
- Experience supporting AI, machine learning or advanced analytics use cases through trusted and well-governed data foundations.
- Experience with data contracts, self-service analytics platforms and modern data governance approaches.
- Familiarity with cloud data technologies such as BigQuery, Snowflake, Databricks or equivalent.
Why Compare the Market?
We’re a business built for pace and performance. Here, you’ll be encouraged to think differently, act boldly, and deliver brilliantly in a culture that values results and rewards progress.
We believe diverse teams make better decisions, and we’re committed to creating an inclusive workplace where everyone feels empowered to grow, contribute, and thrive.
If you’re ready to stretch yourself, raise the bar, and grow with a team that’s serious about performance, innovation, and purpose, we’d love to hear from you.
