> Markdown version of [/jobs/ext/2318346-senior-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/2318346-senior-analytics-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # (Senior) Analytics Engineer - **Company:** bunch - **Location:** Berlin, Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Airflow, Data Analysis, BigQuery, Information Engineering, Data Warehousing, Dimensional Modeling, Python (Programming Language), SQL Databases, Data Ingestion, Pagination - **Published:** August 4, 2026 - **Apply:** https://de.indeed.com/viewjob?jk=599ef86e34d669d4 ## About the Role * Experience: 4+ years in analytics or data engineering, ideally somewhere you owned the whole stack * Modeling: you have real opinions on dimensional modeling, layering and contracts * dbt: you know dbt past writing sql models, so materializations, incremental strategies, macros, CI, and where it breaks * Python: production-quality, with a proper understanding of ingestion (APIs, pagination, incremental loads, schema drift). dlt experience is a bonus * Infrastructure: comfortable owning deployed infra, scheduling with Airflow, Dagster or similar is a plus * Pragmatic: you start from what the business needs and you know when good enough is good enough, * Technical Interview (60 min): a live SQL exercise and a design discussion * Deep Dive (45 min): your track record and how you work * Final Round (30 min): culture, growth, and strategic fit ## Description * Data warehouse: BigQuery * Transformation: dbt * Data ingestion: dlt * BI / semantic layer: Lightdash * Event tracking: PostHog ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [A journey of a long list in React](https://www.wearedevelopers.com/videos/203-a-journey-of-a-long-list-in-react) - [Making Data Warehouses fast. A developer's story.](https://www.wearedevelopers.com/videos/302-making-data-warehouses-fast-a-developer-s-story) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Analyst Salary Germany](https://www.wearedevelopers.com/magazine/277-data-analyst-salary-germany) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market)