Data & Analytics Engineer
Harper's data layer is yours to build. Lay the foundations, connect the systems, and make sure the whole business runs on data it can trust.
We are Harper, a fast-growing Series A startup at the intersection of eCommerce and Fintech.
Our mission is to keep personal service at the heart of the digital shopping experience by enabling elevated Try Before You Buy experiences for some of the world’s leading fashion retailers.
Role overview
We're looking for a Data & Analytics Engineer to own Harper's data; designing the architecture, connecting the sources, and making sure the entire business can query, trust, and act on it. We've recently introduced an AI-assisted querying layer that gives the whole business direct access to our data. Your job is to make sure what it returns is accurate, well-documented, and trustworthy.
You'll work directly with non-technical stakeholders, translating their questions into reliable pipelines and well-defined metrics. You'll bring a product engineering mindset, contributing to feature work where data and product intersect.
Key responsibilities
Design, build, and own Harper's data lake and pipeline infrastructure end to end
Connect & Ingest new data sources as the business scales
Build and maintain a single source of truth
Define and document data quality checks and testing standards to ensure reliability
Build and maintain a comprehensive data dictionary
Structure documentation and definitions so they're optimised for AI agent consumption
Support non-technical colleagues understand which metrics to use, which tables to query, and when something looks off
Collaborate with engineers on product features with a data component
Key skills
Proven experience in a data engineering or analytics engineering role, with hands-on ownership of data infrastructure in a production environment
Strong SQL skills and experience designing data models for a modern data warehouse
Familiarity with most of our core stack (RDS postgres, MongoDB, AWS Athena, Parquet, AWS Glue, Airflow, Python, Docker, S3, Airflow, Python, GraphQL, REST). You're not expected to know all of our tech, but you'll be confident and proficient in your core area.
Familiarity with pipeline orchestration tools incl. Airflow, AWS Glue, Python, or similar
A strong instinct for data quality: testing, validation, and building checks that catch problems before they reach stakeholders
Clear communicator who can explain complex data concepts to non-technical colleagues and translate business questions into data problems
Curious and resourceful, with the instinct to understand the outcome a metric or dashboard is meant to drive, not just the technical spec
Nice to have
Graph database experience, like Neo4JAWS Glue, Python, Docker
Experience with CI/CD pipelines for data workflows
Python proficiency
Experience working in a startup or early-stage environment where you've had to build from scratch rather than inherit existing infrastructure
What we offer
Competitive salary + meaningful share options to build long-term value
Real ownership and autonomy from Day 1, working directly with the founders
32 days holiday (take public holidays whenever you like) with a 3-day carryover policy
£600 annual wellbeing allowance
MacBook and the tools you need to do your best work
Hybrid working and regular team socials
Interview process
20-minute intro video call – a chance for us to get to know you and tell you more about Harper
30-minute technical video call – assessment of your technical skills and problem-solving
90-minute in-person interview – we’ll give you a scenario that we will work through together
Offer 🎉
- Department
- Product
- Locations
- London
- Remote status
- Hybrid
About Harper
Harper provides the UK's leading retailers with Try Before You Buy services.