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 Neo4J, AWS 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
#J-18808-Ljbffr…