Sr. Data Engineer

Role overview

Join a fast-evolving analytics platform serving commerce brands as a Senior Data Engineer. The work centers on building and extending production data systems that ingest multi-channel retail data and turn it into trustworthy, business-ready insights. You'll shape the data foundation that powers operational decisions, AI-assisted recommendations, and scenario planning for thousands of operators.

Responsibilities

- Extend the analytics layer by designing new mart tables, semantic models, and intermediate transformations that respond to evolving business needs. - Investigate and resolve data discrepancies across sales channels, including schema differences, late-arriving data, and idempotent update patterns. - Tune BigQuery performance through partitioning, clustering, and query optimization to keep analytical workloads efficient and cost-aware. - Build tenant-specific analytics and custom reporting that meets the varied needs of multi-channel commerce customers. - Integrate machine-learning forecasting outputs into the analytics workflow, helping productized predictions surface in dashboards and planning tools. - Maintain documentation for the semantic layer, data model patterns, and transformation conventions.

Requirements

- Deep SQL skills applied to complex analytical workloads, with hands-on experience writing and optimizing production queries. - Strong knowledge of columnar data warehouses such as BigQuery, including partitioning, clustering, and cost optimization techniques. - Data modeling expertise in dimensional design, slowly changing dimensions, and fact and dimension table architecture. - Familiarity with e-commerce concepts such as orders, fulfillments, inventory, returns, and multi-channel retail data flows. - Python proficiency for data processing scripts and working with ML pipeline outputs. - A data quality mindset, with experience implementing validation checks and handling edge cases that affect downstream reporting.

Nice to have

- Experience with transformation frameworks such as Bruin or dbt. - Hands-on exposure to ELT tools like Airbyte or comparable ingestion platforms. - Background in multi-tenant data architectures. - Familiarity with demand forecasting or time-series analytics tooling. - Prior work with commerce platform data APIs and their underlying schemas.

Benefits and work setup

- Remote-friendly role with the option to work from Berlin. - Direct impact on a production platform where thoughtful, well-tested changes are valued. - Cross-functional collaboration with product, engineering, and AI teams.