Senior Data Engineer

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.

tem exists 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.

In late 2025, after extraordinary growth, we closed a $75 million Series B – led by Lightspeed Venture Partners with participation from Albion, Atomico, Allianz, Hitachi Ventures, Hitachi Ventures, Schroders Capital and others – positioning us for global expansion, deeper product innovation and category leadership.

We’re scaling internationally and building toward a future where AI-driven infrastructure is foundational to electricity markets worldwide.

Since launch, our modern utility product, known as RED, has already facilitated thousands of business customers and billions in energy transaction value, proving that modern software and AI can transform an industry built on legacy systems.

At tem, we’re not just building another energy company, we’re rearchitecting market infrastructure so that transparency, efficiency and sustainability become the default, not the exception.

THE ROLE

We’re hiring a Senior Data Engineer.

Data sits at the core of what tem does. Our time-series data is the spine that runs from pricing through to billing: every transaction depends on it working. You’ll be working across a genuinely varied set of workloads: textual data, time-series data, and event streams, each with its own ingestion and reliability challenges, including TSDS.

You’ll join our Data Service team of 4, owning the design, reliability, and recovery strategy of specific ingestion pipelines and systems end-to-end. This is an individual contributor role: no team to manage, full ownership of the work you do. The team has more work than hands right now, and this role exists to close that gap so the business can move faster on the data it depends on.

You’ll also work closely with our AI initiatives as they grow: the platform you own increasingly becomes the foundation those efforts depend on.

You will:

– Own the design, reliability, and recovery strategy for the ingestion pipelines and systems in your domain.

– Maintain and improve the data platform, including working through the existing tech debt backlog.

– Build monitoring and alerting so issues surface before they become incidents.

– Set the data quality checks that make an SLA commitment possible, and hold the line on them.

– Help take the number of data products with a defined SLA from 2 to 10.

RESPONSIBILITIES

Data Ingestion

– Own the design, reliability, and resilience of ingestion pipelines end-to-end, including TSDS, with a clear recovery strategy when things break.

– Build and maintain ETL/ELT pipelines for new and existing data sources.

– Decide the right approach (batch vs. streaming) for each pipeline in your domain, including high-scale, low-latency requirements for time-series data.

– Set data quality checks that make an SLA commitment possible, and hold the line on them.

Platform Maintenance

– Own the day-to-day reliability of the data platform: monitoring, testing, and fixing issues before they become firefights.

– Own code quality and standards for the systems you’re responsible for, including CI checks (linting, tests, coverage).

– Work through the existing tech debt backlog, prioritising fixes that unblock SLA commitments.

– Optimise pipelines for performance and cost as data volumes grow.

– Handle the failure modes specific to energy data: late arrivals, reprocessing, backfills.

Monitoring & Alerting

– Build and improve observability across your systems so problems surface before they cause downstream impact.

– Set up alerting tied to the SLAs the team is committing to.

– Investigate and resolve issues within your domain, escalating genuinely cross-system problems.

Supporting Expansion

– Help scope and prepare the platform for new data sources tied to international expansion.

– Flag where current architecture won’t hold up as scope grows, even if fixing it isn’t your call to make alone.

– Work closely with the AI team as their data needs on the platform grow.

REQUIREMENTS

Must haves

– Strong Python skills, with proven experience building and maintaining production data pipelines.

– Experience owning the design, reliability, and resilience of a data pipeline or system end-to-end, not just writing pipeline code.

– AWS or GCP experience.

– Great communication skills, comfortable working directly with stakeholders to scope and agree SLAs, and explaining technical trade-offs to non-technical audiences.

– Strong team player, comfortable working independently against a backlog and making judgement calls on prioritisation, while fitting into an existing team of 4.

– Terraform experience.

Bonus points

– Experience with time-series data at scale.

– Experience with modern data stack tooling (Airflow, Snowflake, BigQuery, Redshift, ClickHouse).

– Experience in energy or climate tech.

– Background in high-growth startups or scale-ups.

– Genuine interest in how AI tooling and workflows intersect with data engineering.

We’re open to someone who doesn’t tick every box here, as long as they bring solid AWS or GCP experience and the ability to own their own work end-to-end.

BENEFITS & PERKS…

Source: EU Remote Jobs (https://euremotejobs.com/job/senior-data-engineer-7/)