At a Glance
- Tasks: Lead the design and evolution of our data platform, shaping technical direction and standards.
- Company: Join a pioneering energy tech company focused on transparency and fairness in electricity transactions.
- Benefits: Competitive salary, stock options, flexible remote work, and generous wellbeing budgets.
- Other info: Dynamic, inclusive culture with opportunities for personal and professional growth.
- Why this job: Make a real impact by building a cutting-edge data platform from the ground up.
- Qualifications: Proven experience in data engineering, strong Python skills, and a product mindset.
The predicted salary is between 105000 - 105000 £ per year.
Who We Are: We are rebuilding the energy transaction, making it transparent and fair. Our goal is to put power back where it belongs, in the hands of customers and to take on one of the most critical problems of our century, access to low cost electricity. We exist to fix a broken global energy market that’s long favoured legacy operators, intermediaries, and opaque pricing. Today’s electricity system was not designed for rapid decarbonisation, AI-driven efficiency or fair access for the actual users - businesses and generators. We’ve built the first AI native transaction infrastructure to reinvent how electricity is bought, sold and priced. Our technology is designed to cut out the inefficient fees, automate complex market flows, and bring transparency and fairness to energy transactions at scale.
The Role: We’re looking for a Staff Data Engineer to lead the design and evolution of our data platform. This is a high-impact, hands-on role combining technical leadership, system architecture, and product thinking. You’ll work closely with engineering, data science, and energy domain experts to ensure that data is reliable, scalable, and directly drives business value. You'll work across the data management service team alongside data and analytics engineers, and in close partnership with energy domain experts, data scientists, and the broader engineering organisation.
What You'll Do:
- Technical Leadership
- Shape the technical direction across batch and streaming pipelines, setting the architecture others build to.
- Set standards for pipeline design and data quality.
- Lead design reviews and mentor other data engineers.
- Evaluate and introduce tooling where it raises the bar — and make the case for when it doesn't.
- Build and maintain robust ETL/ELT pipelines.
- Build systems optimised for high-ingestion, low-latency querying of time-series data (TSDS).
- Optimise pipelines for performance, cost, and reliability.
- Enable self-serve analytics and decision-making across the company.
- Implement data quality frameworks with real teeth: SLAs, automated testing, lineage, and monitoring.
- Establish practices specific to energy data: late arrivals, reprocessing, backfills, and the failure modes that matter in this domain.
- Build the observability layer that makes the platform trustworthy without constant human oversight.
- Identify and fix the bottlenecks that constrain us today.
- Optimise pipelines for performance, cost, and reliability as data volumes grow.
- Architect for the next order of magnitude, not just the next quarter.
- Set engineering standards for pipeline design, data quality, and system observability.
- Lead design reviews and mentor data engineers, raising the bar for how the team works.
- Act as a multiplier: the people around you should get better because of how you approach problems.
What We’re Looking For:
- Experience
- Proven experience operating at staff level (ownership of systems, not just pipelines).
- Experience building and scaling modern data platforms.
- A track record of operating at staff or principal level: you’ve owned systems, shaped technical direction across teams, and influenced how engineering gets done — not just delivered pipelines.
- Deep experience building and scaling production data platforms, including high-ingestion time-series workloads, and strong hands-on ability in Python and modern data stack components (orchestration, warehousing, observability).
- The ability to design for reliability and scale — you understand the tradeoffs in data system design and have made consequential architecture decisions you can speak to clearly.
- A product mindset: you care about whether the data is actually useful and used, not just whether the pipeline ran green.
- Experience with cloud data infrastructure (AWS or GCP) and a point of view on what good looks like.
- The communication skills to lead without authority — influencing technical direction across teams and making the case for the right thing even when it's harder.
- Strong programming skills in Python, with experience building production-grade data systems.
- Experience with modern data stack components (e.g.): Orchestration: Airflow / Dagster; Warehousing: Snowflake / BigQuery / Redshift / ClickHouse; Streaming (nice to have): Kafka / Flink.
- Experience with cloud platforms (AWS / GCP).
- Experience with data observability and testing practices.
- Experience in energy or climate tech.
- Familiarity with time-series data at scale.
- Experience supporting ML pipelines in production.
- Background in high-growth startups or scale-ups.
What Success Looks Like:
- The data platform handles our current scale without firefighting, and is architected for the next phase of growth.
- Other teams can access, trust, and use data without routing requests through the data engineering team.
- There is a tight, reliable feedback loop between data ingestion and consumption: trading, forecasting, and analytics teams make faster decisions because the data is there when they need it.
- The data engineering team has clearer standards, better practices, and higher output than when you arrived.
Benefits & Perks:
- Competitive salary - our current band for this role is £105,000 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.
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 Data Engineer employer: tem
Contact Detail:
tem Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at tem. A personal introduction can make all the difference when it comes to landing that interview.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a project that highlights your experience with data platforms and Python. When you get the chance to chat with the team, having something tangible to discuss can really set you apart.
✨Tip Number 3
Be ready for technical challenges! Brush up on your knowledge of data pipelines and system architecture. Expect to dive deep into your past experiences during interviews, so be prepared to discuss how you've tackled complex problems.
✨Tip Number 4
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 being part of our mission to revolutionise the energy market.
We think you need these skills to ace Staff Data Engineer
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with data platforms and technical leadership. We want to see how your skills align with our mission of transparency and fairness in energy transactions.
Showcase Your Technical Skills: Don’t hold back on showcasing your programming prowess, especially in Python and modern data stack components. We’re looking for hands-on experience, so share specific projects or challenges you've tackled that demonstrate your capabilities.
Communicate Your Vision: We love a product mindset! When you write about your past experiences, focus on how your work has driven business value and improved processes. Show us that you care about the end result, not just the technical details.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team. Let’s get started on this journey together!
How to prepare for a job interview at tem
✨Know Your Data Inside Out
Before the interview, dive deep into your past experiences with data platforms. Be ready to discuss specific projects where you built or scaled data systems, especially focusing on high-ingestion time-series workloads. This will show that you not only understand the technical aspects but also how they drive business value.
✨Showcase Your Leadership Skills
As a Staff Data Engineer, you'll need to demonstrate your ability to lead without authority. Prepare examples of how you've influenced technical direction across teams and mentored other engineers. Highlight situations where your leadership made a tangible difference in project outcomes.
✨Be Ready for Technical Challenges
Expect technical questions that assess your problem-solving skills and understanding of modern data stack components. Brush up on your Python programming and be prepared to discuss orchestration tools like Airflow or Dagster. They might even throw in a scenario to test your architectural decision-making skills!
✨Understand the Energy Sector
Familiarise yourself with the energy market and the challenges it faces, especially regarding transparency and efficiency. Being able to speak knowledgeably about how your role as a data engineer can contribute to solving these issues will set you apart from other candidates.