Data Engineer
New Yesterday
About Apron
Apron was started by a group of people who'd spent years building products for some of today's most successful global fintech companies. But there was one problem that no-one was solving: Business money. The kind that buys tomatoes, tiles, and till rolls. The kind that keeps suppliers happy and business booming. The kind that, before you know it, eats up your entire day.
One million small businesses in the UK will each spend 5 hours this week paying and reconciling invoices, alongside countless hours chasing staff for expense receipts.
This is a problem that's affecting entrepreneurs. Dreamers. Risk takers. Backbones of our communities. Imagine what they could do with this time instead. What would they build? How far could they go? That's why we created Apron as an essential tech layer in the small business machine. We flip the payment experience from blocking business to boosting it. Apron weaves neatly into your workflow and tightens it up, turning hours into minutes.
We have grown fast over the past few years, expanding our team to circa 70 individuals across the UK and more. We are backed by Index Ventures, Bessemer Venture Partners, with participation of Visionaries Club and the founders of Melio and Klarna and we've raised $50m.
About the team
At Apron, many of our teams rely on data - from Payments, Cards, and Invoice Capture to Customer Support. We're also actively developing AI technologies, such as document recognition and invoice detection, that depend on a strong data foundation.
We already have talented data analysts, and many others across the company (product managers, engineers, support) who work with data every day. Our goal is to empower everyone at Apron to explore, understand, and act on data in a self-serve way.
So far, we've built the first version of our data platform usingdbt and Metabase. Now we're taking it to the next level: evolving the architecture to handle more data sources, greater scale, and new use cases from analytics to AI. This includes building a warehouse setup that can grow with us, consolidating company-wide data, and giving every team the tools to use it effectively.
We work on a hybrid basis, at least 3 days per week from our Liverpool Street offices.
What you'll be doing
We're looking for a Senior Data Engineer who can own and lead this evolution of our data platform: making it reliable, scalable, secure, and ready for the next stage of Apron's growth
- Build & run our data platform so it's fast, reliable, and always ahead of the curve.
- Make data self-serve for the whole team - ensuring everything lands in our DWH with the right discovery & cataloging tools in place.
- Set the rules of the road for data governance, privacy, and compliance (GDPR and beyond).
- Keep our data safe by implementing and monitoring security controls.
- Get your hands dirty - this is a hands-on IC role where you'll own the development and support of the platform.
What we're looking for
- 5+ years across Data Engineering.
- SQL & Python: schema design, transformations, query optimisation, automation, testing.
- Track record of buildingETL/ELT pipelines into modern warehouses (BigQuery, Snowflake, Redshift).
- Familiar with tools like Dagster, Airflow, Prefect, dbt, Dataform, SQLMesh.
- Cloud experience (we're on GCP) + containerisation (Docker, Kubernetes).
- Strong sense of ownership over data standards, security, and roadmap.
- Previous startup/tech company/fast-paced experience will be strongly preferred.
- A collaborator at heart - working with analysts, engineers, and product teams to turn data into business impact.
What we offer
- Highly competitive salary
- Stock options
- Health insurance with AXA (including Optical and Dental cover)
- Life Assurance with MetLife
- Enhanced parental leave
- Weekly Deliveroo allowance
- Hybrid setup, with 3 days in the office (Liverpool Street, London)
- Salary sacrifice schemes (Nursery, Cycle to Work, Electric vehicle)
- Fully expensed tech
- Location:
- City Of London
- Job Type:
- FullTime
- Category:
- IT & Technology
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