Analytics Engineer

About This Opportunity

We are representing a confidential fintech organization seeking an Analytics Engineer to join their Product Intelligence team in London. This role sits at the heart of their data infrastructure transformation, building the foundational models and metrics that drive product decisions across the business.

You'll own the data modelling layer that analysts, product teams, and AI tools depend on—creating dbt models, defining metrics, and contributing to the semantic layer that ensures consistent, trustworthy answers. This is an opportunity to build infrastructure rather than just report on existing data, working embedded within a team that's actively migrating to a modern analytics stack.

Responsibilities

• Build and maintain dbt models in a new Analytics Warehouse using clean, layered architecture while migrating logic from legacy systems
• Own tracking plan implementation and quality assurance directly in event tracking platforms, partnering closely with Product and Engineering teams
• Support experimentation frameworks by modelling assignment and outcome data into structured formats for direct querying
• Define and document metrics in the semantic layer to ensure single authoritative definitions across all downstream tools
• Apply AI-augmented data modelling practices as standard in code writing, review, and migration workflows
• Transform one-off analytical questions into durable, reusable data models through collaboration with Product Managers and Analysts
• Maintain data quality through dbt tests, freshness SLAs, and proactive monitoring across your domain

What We're Looking For

• Strong SQL and dbt experience with demonstrated ability to own models end-to-end
• Working knowledge of event-based tracking tools such as Segment or Amplitude
• Experience with Git-based development workflows including opening and reviewing pull requests
• Clear communication skills to explain data definitions and structures to both technical and non-technical stakeholders
• Active, day-to-day use of AI tooling as part of your standard coding and workflow routine
• Comfort navigating ambiguity and untangling legacy logic to build modern data foundations
• Product-led environment experience with both technical execution and stakeholder collaboration

This role is not suitable if: You prefer only building dashboards without owning underlying models, require rigid processes before taking initiative, or prefer to avoid data migration and legacy system refactoring.

Tech stack context: BigQuery data warehouse, dbt transformation, Airflow orchestration, Segment and Amplitude for tracking, modern BI tools

How We Work With You

When you apply through Get A Job.ai, our talent team reviews your submission and conducts an initial screening. We then coordinate your interview process with our client, which includes:

• Introductory call with their Talent Partner (30 minutes)
• SQL assessment via coding platform
• Hiring Manager interview (45 minutes)
• Team interview with live data modelling case
• Final interview with senior leadership (30 minutes)

Please apply only through Get A Job.ai. Do not attempt to contact the client directly, as all applications are managed through our recruiting process.

Location & Work Arrangement

This position is based in London with flexible working options supporting both hybrid and fully remote setups.

Equal Opportunity

Get A Job.ai is committed to fair and equitable recruiting practices. We review every application with care and encourage candidates from all backgrounds to apply, even if you don't meet every single requirement listed.