Analytics Engineer

Good Habitz is building an activation-first product strategy, and the Product Data function is being built from the ground up. As Analytics Engineer, you'll be the discipline's technical backbone, establishing governed, trustworthy models across the data estate and setting the standards the function will run on. You'll work hands-on in Databricks, partnering closely with the data engineer on modelling and with product and business stakeholders on what to measure and why.

This role reports to the Product Data Lead.

• Build trust in the data estate. Assess the Databricks estate, define trust levels, and propose owners for each source and table.
• Model with dbt. Build and version silver-to-gold transformations with dimensional modelling and a semantic layer, designing point-in-time dimensions that preserve history.
• Own the event taxonomy. Design and roll out one event taxonomy and naming convention, partnering with engineering to govern it as a shared contract.
• Define shared metrics. Own the metric catalog and sign-off process, and build activation, engagement and retention models leadership can steer by.
• Enable self-serve. Build semantic models and documentation that let product and business teams answer their own questions.
• Enforce quality. Set data quality standards, build sign-off into a Definition of Done gate, and monitor instrumentation to catch issues early.
• Work with product. Partner closely with product teams so measurement is part of how features are shaped and shipped, not an afterthought.

• Production-level experience with SQL with Git as a working habit
• Experience with dimensional modelling and semantic layers
• Experience building a tracking plan or event taxonomy in partnership with engineering
• A track record of building enforcement processes such as data contracts, CI validation or DoD gates, not just writing standards
• Comfort translating ambiguous product and business questions into clear, durable measurement definitions
• Experience with Databricks/Unity Catalog, B2B SaaS multi-surface products, or data observability tooling is a plus
• Experience working inside a product team, or closely alongside PMs, designers and engineers, where data shaped what got built and not only what got reported

• You'd rather work within an established data estate than build governance and standards from scratch
• You treat a standard as finished once it's written, rather than building the mechanism that makes it stick
• You prefer one-off fixes over designing models built for reuse across a fragmented estate
• You're not comfortable being the first to define "how we do this here" and holding the line once it's set

Welcome to Good Habitz, one of the fastest-growing international EdTech companies in Europe. Our mission? To make learning as accessible, engaging, and fun as binge-watching your favorite series, scrolling through your feed, or watching your team score a winning goal.

We create unique online training experiences available in 10 countries, all produced in-house at the Good Habitz Studios. That's exactly where you'll land: a multidisciplinary team of educational designers, writers, graphic designers, video creatives, and creative producers who turn learning science into experiences people actually want to use.

Become part of the leader online training company in the European market, the benchmark in our sector, and help organisations thrive while you grow professionally at a trailblazing company with unstoppable momentum on an exciting growth journey even as others in the industry face challenges.

• Competitive salary and role-specific performance bonus because we value your contributions and…