Senior Analytics Engineer

Senior Analytics Engineer
Function: Data
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.

At Compare the Market, we’re a purpose-driven business powered by tech and AI. We’re building high-performing, results-driven teams with the skills, mindset, and ambition to deliver outcomes at pace. Every role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers.

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: 

We’re looking for a Senior Analytics Engineer to lead the design and evolution of scalable analytics solutions that power a modern, self-serve analytics platform. 

This role is ideal for someone who enjoys solving complex technical challenges, influencing engineering direction, and driving high standards across analytics engineering practices. You will provide technical leadership across domains, shape scalable data foundations, and partner closely with Product, Analytics, Technology, and Data Platform teams to deliver trusted, high-impact data solutions at scale. 

Some of the great things you’ll do: 

• Lead and deliver complex, high-impact analytics engineering initiatives across multiple teams or product areas.  

• Own the architecture and evolution of key data models, transformation pipelines, and analytics workflows.  

• Design scalable, performant, and maintainable analytics solutions aligned to business priorities and engineering standards.  

• Shape technical direction in partnership with Data Platform and Technology leadership, contributing to architecture and roadmap discussions.  

• Drive improvements in data quality, observability, resilience, and operational excellence across the analytics stack.  

• Reduce technical debt and improve developer experience through better tooling, automation, standards, and engineering practices.  

• Mentor and support engineers across the team through technical guidance, coaching, feedback, and knowledge sharing.  

• Collaborate closely with Product, Analytics, Engineering, and business stakeholders to align on outcomes and reduce delivery risk.  

• Build and support reporting and BI solutions that enable scalable decision-making across the organisation.  

• Champion analytics engineering best practices including testing, documentation, CI/CD, and code review.  

• Lead or contribute to platform initiatives such as migrations, governance improvements, model refactoring, and platform modernisation.  

• Represent Analytics Engineering in technical forums and cross-functional strategy discussions.  

• Foster a culture of inclusion, collaboration, accountability, and continuous improvement. 

What we’d like to see from you: 

• Advanced SQL and strong hands-on experience with DBT and modern analytics engineering practices.  

• Proven experience designing scalable, analytics-ready data models and transformation frameworks.  

• Strong understanding of data modelling, performance optimisation, testing, and data reliability practices.  

• Experience delivering reporting and BI solutions from discovery through to production adoption.  

• Comfortable operating in modern engineering environments using Git, CI/CD, automation, and infrastructure-aware development practices.  

• Ability to lead technical initiatives and influence engineering direction across teams.   

• Strong stakeholder management, communication, and collaboration skills. 

• A pragmatic, outcome-focused mindset with a passion for building reusable and trusted data solutions. 

Nice to have: 

• Experience with Databricks, Spark, Airflow, or distributed data processing technologies.

• Experience supporting enterprise data platform migrations or modernisation programmes. 

• Familiarity with observability tooling, data governance, and data platform operations. 

• Experience mentoring engineers or contributing to team capability uplift initiatives.