Principal Analytics Engineer

To make that real, we need someone to set the technical bar. As Principal Analytics Engineer (f/m/d) you define the lakehouse architecture and the standards that let teams move fast without fragmenting, you embed in the Product Data Domain to ship genuine data products, and you raise the craft of everyone around you. This is a hands-on technical leadership role with real autonomy. You shape how we build, not just execute a backlog., * Architecture, with the teams. Define and evolve the lakehouse architecture (S3 + Apache Iceberg + Athena + dbt): table and layer design, partitioning and compaction, schema evolution, multi-team isolation, and unified catalog & discoverability. You design together with the teams, not in isolation

• Standards that make data products real. Modeling conventions, the semantic layer, data-product definitions, testing and data-quality, CI/CD, documentation and metadata, so products are reliably consumable by humans, APIs, and AI agents alike

• Exemplary delivery. Build data products in the Product domain that set the pattern others follow. You ship, not just advise

• AI-ready data. Design metadata and semantic layers so agents query our metrics correctly; pioneer concrete AI use cases in the build workflow (AI-assisted modeling, testing, documentation, review)

• Spotting what’s next. Track the lakehouse, analytics-engineering, and AI landscape; run lightweight evaluations; and drive adoption of approaches that earn their place

• Growing people. Mentor analysts and engineers, raise review quality, create technical clarity, and constructively question the status quo

Why Join Trusted Shops?

• Personal Development: You’ll receive direct support from your Engineering Manager, ensuring your growth and success
• Health & Wellbeing: Participate in monthly health activities and earn an extra vacation day for achieving health goals
• Continuous Learning: Enjoy your “Self Education Day” every last Friday of the month, where you can focus on personal growth, attend internal tech talks, read a book, or work on your goals
• Inclusive Work Culture: Flexible working options and a focus on work-life balance. No late-night work expected
• If you want to know more about our organisation, feel free to check out the LinkedIn articles of our CTO

• Deep, hands-on lakehouse experience. You have designed and built lakehouse architectures not just used one. You are strong with open table formats (Apache Iceberg or equivalent), object storage (S3), serverless query engines (Athena or equivalent), and dbt
• Excellent analytics-engineering craft. Data-product and dimensional modeling, testing, CI/CD, and a real instinct for query performance and cost
• Demonstrated technical leadership beyond a single team. You have set standards or architecture that other teams adopted, and you can influence without formal authority
• A product mindset. You treat data as a product with consumers and SLAs, including non-human consumers (APIs, AI agents)
• Concrete, hands-on AI experience in your own work, plus genuine curiosity and a bias toward responsible experimentation
• Comfort with autonomy and ambiguity. You set direction, make calls, and bring people with you

• Workation: Temporarily work from a destination of your choice within the EU, Iceland, Liechtenstein or Norway
• Permanent contract with Europe’s trusted brand
• One “Self Education Day” per month
• 28 vacation days + 2.5 additional days off at Christmas, New Year’s Eve and Carnival
• Buddy programme (an experienced trustee is at your side)
• Individual training opportunities
• Events (Team Events, Unit Events, etc.)
• Health Pass (free online and offline sports, fitness and health courses)

BUILD A COMMUNITY OF TRUST WITH US - #cometotrust

Not sure if you are what we are looking for? Apply! At Trusted Shops, we are interested in you as a person - whether you fit in with us is independent of gender, nationality, ethnic and social origin, religion/belief, disability, age, sexual orientation and identity. Trusted Shops is clearly committed to diversity and against discrimination.

Data Services is shifting from being strong in raw data to reliably delivering prepared, standardized data products as the foundation for self-service reporting, product-facing APIs (Metrics-as-a-Service), and AI/agent access (e.g. via MCP). We are building these products inside one shared Data Lakehouse, where multiple domain teams build to a common standard.