Senior Analytics Engineer

Senior Analytics Engineer

We're looking for a Senior Analytics Engineer to help build and shape the analytics foundation of a growing startup.

You'll join a small data team and work on the analytics layer end-to-end: core data models, trusted metrics, and the patterns that enable the rest of the company to use data with confidence. This is a hands-on, individual contributor role (no people management), with significant technical ownership across the business.

You'll work primarily with dbt for transformations and Omni as our semantic and analytics layer, partnering closely with Marketing, Finance, Operations, and Data Engineering. In your first few months, you'll get fully up to speed on our warehouse and dbt project and start shipping production-ready models, take ownership of at least one core business area (e.g. Marketing or Revenue metrics) to improve structure, documentation and consistency, and build strong relationships with stakeholders — becoming a trusted point of contact for analytics questions.

Responsibilities

• Build and maintain the analytics layer: Design, build, and maintain core dbt models that represent the business (e.g. customers, revenue, marketing performance, operations) and keep them production-ready — contributing to the source of truth the business operates on.

• Implement and document company metrics: Partner with stakeholders to understand metric needs, translate them into clear definitions, and implement them in Omni so teams can self-serve with confidence.

• Deliver cross-functional analytics projects: Work across multiple domains and teams to ship high-impact analytics work — coordinating with stakeholders, managing your own sequencing, and seeing projects through to done.

• Make pragmatic modelling trade-offs: Balance speed, accuracy, and long-term maintainability; contribute to patterns that scale as the company grows.

• Raise data quality and trust: Apply dbt tests, CI/CD, and documentation standards to catch issues early and reduce regressions.

• Partner upstream to fix root causes: Work closely with Data Engineering to diagnose data issues, improve source/warehouse design, and keep the warehouse performant and reliable.

Requirements

Must-haves

• Strong hands-on experience as an Analytics Engineer in a fast-moving environment.

• Deep, practical dbt experience, including:

  • Incremental models

  • Custom macros

  • Debugging and optimising slow or expensive models

  • Project structure and maintainability

• Excellent SQL and solid data modelling fundamentals.

• Experience with a semantic layer or BI modelling tool (Omni, Looker, or similar).

• Experience translating business questions into metric definitions with stakeholders.

• Comfortable working with ambiguity and limited process.

Nice-to-haves

• Experience working with Marketing and Finance data.

• Exposure to early-stage analytics stacks or building analytics from scratch.

• Familiarity with experimentation, funnel analysis, or unit economics.

Benefits & Perks:

Salary: Competitive salary — we are looking to pay £85,000 or equivalent in local currency.

We review salaries twice a year using real-time market data, with transparent, consistent pay for the same role and level.

Stock Options: Everyone on the team has ownership in our mission.

25 days holiday + public holidays: Swap public holidays for ones that matter most to you. Plus, get an extra day off for your birthday.

Remote & flexible working: We're fully remote, distributed across Europe with clear core hours, and no internal meetings on Friday afternoons.

Home working & wellbeing budgets:

• Up to £1,200 / €1,200 annually to upgrade your remote setup (co-working passes, equipment, etc.).

• Up to £150 / €150 monthly on anything that supports your wellbeing — from therapy to gym memberships to meditation apps.

Interview Process:

Our processes normally take around 2-3 weeks from first call to offer — please let us know about any adjustments to timelines that may be required.

First call with our Talent Team (30 mins): This is to understand your experience, motivations, and discuss the role in more detail.

Behavioural Interview with our Data Manager (75 mins): This is your chance to really understand the role, the expectations, and ensure alignment on ways of working.

Technical Interview with the Team (60 mins): You'll meet with potential peers in this session and work through a live technical exercise.

Culture-Add Interview with Stakeholders (45 mins): The final session will be with two cross-functional stakeholders, and will explore how your values align with ours. It's designed to be a genuine two-way conversation — your chance to understand what it's really like to work at tem.

We welcome applications from people of all backgrounds, experiences, and identities, including those that are traditionally underrepresented in the tech and energy sectors. If you're excited about this role but not sure you meet every requirement, we'd still love to hear from you. Your unique perspective could be exactly what we're looking for.