Senior Data Engineer

Posted Yesterday
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Hiring Remotely in UK
Remote
60K-74K Annually
Senior level
Software
The Role
Design, build, and own scalable data pipelines from ingestion through analytics and incentive payouts. Lead data platform architecture, including Snowflake, dbt, Iceberg, and S3 workflows. Establish data quality, lineage, observability, performance, cost, and SLA standards. Partner with engineering and analysts to support telematics accuracy and driver incentive reporting. Develop maintainable data models and transformation layers while using AI coding tools to improve development speed and quality.
Summary Generated by Built In
About ev.energy
We are building the world's largest EV-centric virtual power plant (VPP). By connecting to vehicles, chargers, batteries, solar, and other distributed energy resources, we turn households into flexible grid assets that balance supply and demand, preventing blackouts and reducing reliance on fossil fuels.
We are scaling rapidly across North America and Europe. We are moving fast, we are AI-first, and we are looking for builders who want to power the grid of the future.
About the role
Data is at the heart of everything ev.energy does — from measuring charging events and grid impact to calculating the utility incentives we pay drivers. As we scale our data function, we're hiring a Senior Data Engineer to lead the design of our warehousing architecture and own our pipelines end-to-end, from ingestion through to the analytics and payouts they power.
What we're looking for
  • 5+ years in data engineering (or backend engineering with a heavy data focus)
  • Hands-on at scale with a cloud warehouse (Snowflake ideally) and dbt; strong Python and SQL; solid data modeling, warehousing, and schema design
  • Comfortable owning systems end-to-end in a fast-moving environment — you build it, you run it
  • Already using AI coding tools day-to-day and excited to push how far they go
Also nice to have
  • Experience supporting production ML or real-time analytics workflows
  • Familiarity with CDC / streaming (Apache Iceberg, S3) and BI tooling (Holistics, Hex)
  • Background in energy, IoT, payments, or another high-volume, correctness-critical domain

What you’ll do
  • Design, build, and own scalable data pipelines across our modern data stack (Fivetran, Snowflake, dbt, with Holistics and Hex for analytics), from ingestion to warehousing to delivery
  • Lead architectural decisions across the data platform — including infrastructure like our OLake → Iceberg → Snowflake pipeline — setting technical direction and establishing performance and cost baselines
  • Own data quality, lineage, and observability: freshness, completeness, schema-drift detection, cost-per-job, and SLAs — the correctness our incentive payouts depend on
  • Partner with engineering and analysts on projects like telematics accuracy and the driver incentive reporting, turning business requirements into reliable, well-modeled data
  • Model data for both operational and analytical use cases, and build the dbt transformation layers (staging / intermediate / mart) that keep it maintainable and transparent
AI-first development
  • Use AI tooling (Claude, Cursor, and equivalents) as a core daily practice — to build pipelines, write and review SQL and dbt models, and move faster without cutting corners on quality
  • Our team runs on AI-native infrastructure (agentic routines, shared skills, an internal competency framework); you'll use it, improve it, and bring the best of the ecosystem back to the team

Benefits
The salary range for this role is £60,000-£73,500 GBP.
Key benefits include:
  • Equity - you'll own a part of the business through our share options program
  • Healthcare options - to help keep you and your family in tip-top condition (provided by Bupa & Medicash)
  • Life assurance of 4x your salary
  • Co-working access via WeWork (if you'd like it)
  • Annual 'Team Week' whole company offsite
  • L&D allowance of £1,000 per year - everyone is learning, developing and challenging themselves so we have a professional development fund per year for you to learn new skills
You can find out more about our full range of perks and benefits here.
Location & how we work
This role is fully remote in the UK.
The majority of people at ev.energy work on a fully remote basis, with a small number of roles based on-site in our testing sites.
This means that most of our people work from home, but we're happy to provide co-working subscriptions if you'd like to spend time at a WeWork (or other co-working space close to you).
We balance our remote set up by getting everyone together once a year for an offsite, as we know that spending time together IRL is super important.
Belonging at ev.energy
We are an equal opportunity employer and value diversity: we do not discriminate based on race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. If you'd like a copy of our DE&I policy you can reach us at [email protected]. We'll always do our best to accommodate reasonable adjustments to the interview process if needed - just let us know.

Skills Required

  • 5+ years of experience in data engineering or backend engineering with a heavy data focus
  • Hands-on experience with cloud data warehouses, ideally Snowflake
  • Experience with dbt
  • Strong Python skills
  • Strong SQL skills
  • Experience with data modeling, data warehousing, and schema design
  • Ability to own systems end-to-end in a fast-moving environment
  • Daily use of AI coding tools
  • Experience supporting production machine learning or real-time analytics workflows
  • Familiarity with CDC or streaming, Apache Iceberg, and Amazon S3
  • Familiarity with Holistics or Hex BI tooling
  • Experience in energy, IoT, payments, or another high-volume, correctness-critical domain
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The Company
HQ: London
106 Employees
Year Founded: 2018

What We Do

The ev.energy app is the simpler, cheaper and greener way to charge an electric vehicle. Our algorithm enables EV drivers to charge when energy is least expensive and carbon-intensive, whilst balancing demand on the energy grid at peak times. We call it a win-win-win.

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