Staff Analytics Engineer

Staff Analytics Engineer

Full-Time 80000 - 120000 € / year (est.) No home office possible
tem

At a Glance

  • Tasks: Build and shape the analytics foundation for a revolutionary energy startup.
  • Company: Join tem, a game-changer in the energy market focused on transparency and fairness.
  • Benefits: Competitive salary, stock options, flexible remote work, and wellness budgets.
  • Other info: Dynamic team culture with opportunities for personal and professional growth.
  • Why this job: Make a real impact in the energy sector while developing your analytics skills.
  • Qualifications: Strong experience in analytics engineering and proficiency in dbt and SQL.

The predicted salary is between 80000 - 120000 € per year.

Who We Are: We have built the new way for energy to be transacted. tem exists to fix a creaking energy market. Today's wholesale system is stacked in favour of the few - a relic of the oil and gas era, riddled with markups and middlemen. We're changing that. Our product, RED™, is built on a proprietary pricing engine that bypasses the wholesale market, enabling businesses to buy energy produced by renewable generators directly. That means clear, auditable transactions that ensure affordable bills and fair compensation - giving every business real ownership and control over where their energy comes from. Since launching in 2021, we've saved UK businesses and generators over £25 million, powering a growing network of forward-thinking companies, from Pizza Pilgrims to Silverstone. Backed by top-tier VCs including Atomico and Albion, we're creating a new category in energy - one that's decentralised, direct, and built on trust.

The Role: We’re looking for a Staff 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 and influence. 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 design decisions.

Responsibilities:

  • Advance the analytics layer end-to-end: Design, build, and maintain core dbt models that represent the business (e.g. customers, revenue, marketing performance, operations) and keep them production-ready.
  • Define and evolve company metrics: Partner with stakeholders to create clear, consistent metric definitions, and implement them in Omni so teams can self-serve with confidence.
  • Lead cross-domain initiatives: Deliver high-impact analytics engineering projects that span multiple domains and teams—driving alignment, sequencing work, and shipping outcomes.
  • Make pragmatic modelling trade-offs: Balance speed, accuracy, and long-term maintainability; set patterns that scale as the company grows.
  • Raise data quality and trust: Introduce and maintain standards using dbt tests, CI/CD, documentation, and lightweight governance; 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 experience as an Analytics Engineer in a fast-moving environment.
  • Ability to set direction for analytics engineering (patterns, standards, strategy) and execute hands-on.
  • Deep, hands-on dbt production experience, including incremental models at scale (we ingest ~1B rows daily), custom macros, debugging and optimising slow/expensive models, dbt project architecture and maintainability.
  • Excellent SQL and strong data modelling fundamentals.
  • Experience with a semantic layer / BI modelling tool (Omni, Looker, or similar).
  • Proven experience defining metrics with business stakeholders.
  • Comfort operating with ambiguity and limited process.

Nice-to-haves:

  • Experience working closely 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:

  • Competitive salary – our current band for this role is £100,500 or equivalent in local currency.
  • 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. Behaviour Interview with our Data Manager (60 Mins). This is your chance to really understand the role, the expectations, and ensure alignment on ways of working. Technical Interview with the Team (90 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, and is 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.

Staff Analytics Engineer employer: tem

At tem, we are not just transforming the energy market; we are committed to fostering a vibrant and inclusive work culture that empowers our employees. As a Staff Analytics Engineer, you will enjoy competitive salaries, stock options, and generous holiday allowances, all while working remotely within a supportive team that values your contributions and encourages professional growth. Join us in making a meaningful impact on the energy landscape, where your expertise will help shape the future of sustainable energy transactions.

tem

Contact Detail:

tem Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Analytics Engineer

Tip Number 1

Network like a pro! Reach out to folks in the industry, especially those already working at tem or similar companies. A friendly chat can give you insider info and maybe even a referral!

Tip Number 2

Prepare for your interviews by diving deep into dbt and analytics engineering concepts. Brush up on your SQL skills and be ready to discuss how you've tackled data challenges in the past.

Tip Number 3

Showcase your passion for renewable energy and how it aligns with tem's mission. Share examples of how you've used data to drive decisions and improve processes in previous roles.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.

We think you need these skills to ace Staff Analytics Engineer

Analytics Engineering
dbt
SQL
Data Modelling
Semantic Layer / BI Modelling Tools
Metric Definition
Cross-Domain Collaboration

Some tips for your application 🫡

Show Your Passion:When you're writing your application, let your enthusiasm for the role and our mission shine through. We want to see why you're excited about joining us at tem and how you can contribute to our vision of transforming the energy market.

Tailor Your Experience:Make sure to highlight your relevant experience as an Analytics Engineer. Use specific examples that demonstrate your skills with dbt, SQL, and data modelling. We love seeing how your background aligns with what we're looking for!

Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and focus on communicating your ideas effectively. This will help us understand your thought process and how you approach problem-solving.

Apply Through Our Website:We encourage you to submit your application directly through our website. This ensures that your application gets to the right people quickly and helps us keep track of all applicants efficiently. Plus, it’s super easy!

How to prepare for a job interview at tem

Know Your Stuff

Make sure you’re well-versed in dbt and SQL, as these are crucial for the role. Brush up on your experience with incremental models and custom macros, and be ready to discuss specific projects where you've applied these skills.

Understand the Business

Familiarise yourself with tem's mission and how they’re changing the energy market. Be prepared to discuss how your analytics work can directly impact their goals, especially in areas like marketing and revenue metrics.

Prepare for Technical Challenges

During the technical interview, expect to tackle a live exercise. Practice debugging and optimising slow models beforehand, and think about how you would approach building a core dbt model from scratch.

Show Your Collaborative Side

Since this role involves working closely with various teams, be ready to share examples of how you've successfully partnered with stakeholders in the past. Highlight your ability to communicate complex data concepts in a way that everyone can understand.