Data Engineer

Turn operational data into reliable datasets that help restaurants and internal teams understand performance.

The job

You will build the data foundations behind useful reporting on orders, customer activity and merchant adoption. The role starts with definitions and trust: teams need to agree what a completed order means before comparing revenue or conversion. You will work with product and commercial colleagues to shape practical datasets, maintain quality checks and keep data access appropriate to its purpose.

What you would be doing

• Build and maintain pipelines that transform operational records into usable reporting datasets.
• Define shared metrics with stakeholders and document how they are calculated.
• Implement data-quality checks for completeness, duplication and unexpected changes.
• Manage incremental processing, backfills and schema evolution safely.
• Keep restaurant data separated and restrict access to sensitive fields.
• Optimise slow transformations and queries using measured workload information.
• Support dashboards and investigations with clear, reproducible datasets.

What we are looking for

• Strong SQL skills and practical experience building data transformations or pipelines.
• Experience with Python or another suitable language for data processing.
• Understanding of relational modelling, incremental loads and data-quality checks.
• Ability to investigate differences between source records and reported metrics.
• Clear communication with stakeholders about definitions, limitations and data freshness.

Useful, but not essential

• Experience with dbt or a comparable transformation framework.
• Familiarity with product analytics and commerce reporting.
• Experience designing privacy-aware analytics datasets.

Tools you might use

• SQL
• PostgreSQL
• Python
• Dbt
• BI tools
• Version control

Your first 90 days

• Days 1–30Document key source datasets and agree definitions for a small set of operational metrics.
• Days 31–60Deliver a reliable dataset with automated checks and a repeatable refresh process.
• Days 61–90Support a useful dashboard or analysis and demonstrate how data issues are detected and resolved.

The practical bits

• 2 days per week in the Birmingham office and 3 days working remotely within the UK.
• 37.5 hours per week, Monday–Friday. Core collaboration hours are agreed with the team.
• Occasional planned team or customer visits; approved expenses are reimbursed.

What we offer

• 30 days of annual leave plus public holidays
• A company pension contribution
• A £1,000 annual learning budget for courses, conferences or professional development
• A company laptop and role-appropriate equipment; engineering roles include a development setup
• Flexible start and finish times, agreed with your team around customer and collaboration needs
• Wellbeing support and regular development conversations with your manager
• Reimbursement of approved business travel and customer-visit expenses