Senior Analytics Engineer - Run & Grow

The Run & Grow Tribe of Tribes powers the systems, insights, and experiences that keep millions of merchants engaged, successful, and growing with SumUp across every market we operate in. We're at a genuine inflection point in how we use data, moving from fragmented pipelines to a world-class data foundation built on stable business domains, trusted metrics, and AI-ready data products. This is a greenfield opportunity to shape how data is owned, defined, and built at scale, and as our Analytics Engineer, you'll be the connective tissue that makes that vision real.

What you'll do

• Partner with squads across the tribe on event design and data contracts, maintaining staging pipelines, applying modelling conventions, and keeping domain outputs consistent, tested, and discoverable
• Model key business domains, including merchant activity, product adoption, lifecycle events, and risk scoring, building well-documented, quality-assured data products that serve as the trusted source of truth across the organisation
• Build and maintain the insights layer on top of governed domains, producing reusable KPI models, funnels, cohorts, and segmentations that Product, Commercial, and AI teams can self-serve with confidence
• Implement technical improvements including incremental processing strategies, performance optimisations, and scalable data architecture to support growing data volumes
• Contribute to SumUp's broader data domain strategy, helping establish durable ownership, consistent definitions, and a shared catalogue of data products that unlock self-serve analytics and AI at scale

You'll be great for this role if…

• Strong, proven experience in analytics engineering or data engineering, with a track record of building and maintaining production data systems
• Expert-level SQL skills for complex transformations and query optimisation, with hands-on experience building layered data models in a modern data warehouse or lakehouse (e.g. Snowflake, Iceberg) and solid command of dbt, including testing, documentation, and modelling conventions
• Ability to think in terms of business domains, not just tables, translating complex business logic into clean, durable, and reusable data models across entities, events, states, and rules
• Comfort working across squads with Product Managers, Engineers, Analysts, and Data Scientists, contributing to data design conversations and helping teams treat data as a first-class deliverable
• Deep care for data quality, trust, and discoverability, building models others can rely on, with a proactive mindset around contracts, freshness,