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- Tasks: Design and own data architecture, ensuring reliable access and quality for the whole business.
- Company: Fast-growing Series A startup at the intersection of eCommerce and Fintech.
- Benefits: Competitive salary, share options, 32 days holiday, and a £600 wellbeing allowance.
- Other info: Enjoy hybrid working, autonomy from Day 1, and regular team socials.
- Why this job: Join a mission-driven team and make a real impact in the digital shopping experience.
- Qualifications: Experience in data engineering, strong SQL skills, and ability to communicate complex concepts.
The predicted salary is between 50000 - 60000 £ per year.
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.
We are 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 have 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 will work directly with non-technical stakeholders, translating their questions into reliable pipelines and well-defined metrics. You will 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
- 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, GraphQL, REST)
- 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
- 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
- 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
- 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
Data & Analytics Engineer employer: Harper
Contact Detail:
Harper Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data & Analytics Engineer
✨Tip Number 1
Get to know Harper and its mission inside out. When you’re chatting with us, show that you understand our focus on personal service in the digital shopping experience. This will help you connect with us on a deeper level and demonstrate your genuine interest.
✨Tip Number 2
Prepare for the technical call by brushing up on your SQL skills and familiarising yourself with our core stack. We want to see how you think through problems, so practice explaining your thought process clearly and confidently.
✨Tip Number 3
During the in-person interview, don’t just focus on the technical aspects. Be ready to discuss how you can translate complex data concepts for non-technical colleagues. Show us your communication skills and how you can bridge the gap between data and business needs.
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows us you’re proactive and keen to be part of our team from the get-go.
We think you need these skills to ace Data & Analytics Engineer
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Data & Analytics Engineer role. Highlight your relevant experience with data infrastructure and any specific tools mentioned in the job description. We want to see how you fit into our mission at Harper!
Showcase Your Skills: Don’t just list your skills; demonstrate them! Use examples from your past work to show how you've designed data models or built pipelines. We love seeing real-world applications of your expertise, so let us know how you’ve made an impact.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to explain complex concepts, especially if you're discussing technical details. Remember, we want to see how well you can communicate with non-technical stakeholders!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining the Harper team!
How to prepare for a job interview at Harper
✨Know Your Data Stack
Familiarise yourself with the core technologies mentioned in the job description, like SQL, AWS, and Python. Be ready to discuss how you've used these tools in past projects, as this will show your hands-on experience and confidence in your core area.
✨Communicate Clearly
Practice explaining complex data concepts in simple terms. Since you'll be working with non-technical stakeholders, being able to translate their questions into data problems is crucial. Think of examples where you've successfully communicated technical information to a non-technical audience.
✨Show Your Problem-Solving Skills
Prepare for the technical video call by brushing up on your problem-solving techniques. You might be given a scenario to work through, so think about how you would approach building a data pipeline or ensuring data quality checks. Be ready to demonstrate your thought process.
✨Emphasise Your Curiosity
Harper values curiosity and resourcefulness. Be prepared to discuss how you've approached understanding metrics or dashboards in the past. Share examples of how you've gone beyond just the technical specs to understand the business impact of your work.