Full-stack Engineer (Data)
Full-stack engineer with a data focus at Volter, an AI-native operating system for business energy. You'd own ETL pipelines (meter reads, market prices, tariffs, weather), data modelling of time-series data, and ship product features end-to-end using Go/Python, TypeScript/React, AWS and Terraform, working from the Old Street office 4 days a week.
- Compensation
- Not disclosed
- Location
- London, United Kingdom
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Not specified
- Experience
- Not specified
- Category
- Fullstack
- Posted
Skills
Must have
- Several years as a broad-based software engineer, owning complex features and systems end-to-end in production
- Hands-on data engineering: built and run ETL pipelines and worked deeply with databases in data-intensive systems, ideally time-series
- Strong data fundamentals: database technology choices (OLTP, OLAP), schema design, data modelling, query optimisation, data quality
- Product instincts: enjoys shipping user-facing features as much as building pipelines
- Proficiency across the stack: backend in Go and/or Python, frontend in TypeScript and React, cloud deployment (AWS), infrastructure-as-code (Terraform)
- Fluency in AI-driven engineering with day-to-day use and established processes for high standards
- Confidence to challenge the status quo, make sound calls in ambiguity and advise the team as a peer
Nice to have
- Experience in energy, utilities or another data-heavy, regulated market such as fintech
- Building at an early-stage startup, balancing speed with technical debt
- Previous experience working with data scientists on forecasting or modelling
- Event-driven architectures and security-aware development (least privilege, auditability, PII handling)
Full description
About Volter
AI and renewables are the 21st Centuries two largest megatrends and they're colliding in the world's largest industry: energy. AI has made intelligence abundant, so human brains are no longer the bottle neck, cheap and secure power is.
About Volter
AI and renewables are the 21st Centuries two largest megatrends and they're colliding in the world's largest industry: energy. AI has made intelligence abundant, so human brains are no longer the bottle neck, cheap and secure power is.
The people, businesses and countries that have access to cheap, clean and secure power will lead this century. Renewables can deliver it, but they’ve turned a previously static predictable commodity into a huge complex changing forecasting and optimisation problem that the industry’s decades-old systems were never built to solve.
Volter exists to solve it. We’re building the first AI native operating system for business energy, so that every business can run on power that’s cheaper, cleaner and more secure. Octopus and Kraken did this for homes; we’re doing it for business.
And it’s working. We launched our platform in early 2026 and have already 20x revenue with customers from all across the UK now using the Volter platform. We’re still a small team, so you’ll shape the product, the tech and the culture from the ground up.
Where you plug in
Our platform runs on data: half-hourly meter reads, market prices, forecasts, trades and tariffs all feed the products that price, match, and bill our customers' energy. We’re hiring a Senior Engineer with a data-oriented bent to own and scale our data foundations, while building the product on top of them. In your first year, success looks like data pipelines the business trusts, faster and more reliable pricing and billing, and a product that you've shipped end-to-end that customers and our ops team use every day.
What You'll Power
- Build and own the pipelines that bring data into Volter: half-hourly meter feeds, market and price data, network tariffs, weather data, and other third-party sources.
- Own our data foundations: schema design, data modelling (lots of time-series), query performance and data quality, so our customers and partners can rely on it.
- Ship product features end to end, from data/backend services and APIs through to the customer-facing flows on top of them.
- Shape what we build with commercial, ops and data science: understand the real problem, scope a v1, then measure it and decide what comes next.
- Challenge how we do things: bring your experience to architecture decisions, name the trade-offs and push back when there's a better way.
- Partner with our data scientists to improve forecasting and pricing models.
- Run what you build in production, with logging, monitoring, and alerting that keep it reliable.