Staff Data Engineer

We’ve built a system that predicts various signals about the electricity system on a 72 hour horizon, worldwide. Now we’re in the process of expanding the dimensions, horizons, and granularity of our forecasts. We’re building a platform that can generate high-quality forecasts without requiring bespoke engineering effort for each signal or geographical area.

We’re looking for a Staff Data Engineer who can architect and scale ML infrastructure to support this next stage of growth. You’ll own critical systems end-to-end, designing pipelines that enable reliable, high-quality forecasts without bespoke engineering per signal or region.

About Electricity Maps 🌎

Electricity Maps is on a mission to accelerate the transition to a decarbonized electricity system. Our platform provides real-time and forecasted electricity data, helping companies like Google and Cisco to unlock flexibility and reduce emissions.

• Our free map product is used by millions of people around the world
• Our API powers products at some of the world’s largest enterprises
• We’re backed by top-tier investors with deep experience scaling developer-first, climate-focused companies

What You’ll Build and Own 🧱

You’ll work on data pipelines, feature stores, and ML infrastructure that is flexible enough to predict multiple signals in over 350 regions around the world.

Today, our signals are:

• Load
• Day-ahead prices
• Carbon intensity
• Renewable energy %
• Electricity mix (all generation sources)

We have the vision to keep adding more signals and features to our forecasting platform such as: balancing prices and curtailment.

You’ll:

• Shape and build solutions with our lead and other engineers on the team
• Ship fast, iterate based on real feedback, and own your work in production
• Refine how we build, deploy, and scale across the stack

You’ll Thrive Here If You… 🔍

• Have 8+ years of experience in data or software engineering, including experience building and scaling ML platforms or data infrastructure (but more importantly, have owned complex ML systems end-to-end and seen them evolve and scale in production).
• Have architected and scaled ML systems in production (feature stores, model registries, inference, monitoring)
• Have deep experience with time series forecasting and large-scale data processing
• Take ownership from design to deployment, and make pragmatic technical decisions independently without over-engineering it.
• Care about delivering real value to users
• Mentor and elevate peers through code reviews, pairing, and design discussions

Our stack: Python, PostgreSQL, BigQuery, and GCP. No need for exact matches 🫶🏻 just be comfortable working across modern data platforms.

Bonus points if you…

• Bring experience from the energy and electricity markets domain

Role Details📍

• Full-time
• Based in Copenhagen
• Competitive salary + stock options
• 6 weeks vacation + full health insurance