Staff Data Platform Engineer (m/f/d)
Staff-level, hands-on IC (no people management) who builds and owns adsquare's shared data platform — ingestion, lakehouse, catalogs, databases and AI-agent tooling — at the intersection of DevOps and data engineering, handling TB-scale geo-spatial and location data. Core stack: Python, SQL, Spark, AWS, Apache Iceberg, Terraform, Kubernetes.
- Compensation
- €90K–€105K / yr
- Location
- Berlin
- Work setup
- Not specified
- Seniority
- Staff
- Employment
- Not specified
- Experience
- 7+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 7+ years in Data Engineering, Data Platform or Backend Engineering, including senior/staff-level time with platform-wide scope, still hands-on
- Deep experience designing and operating lakehouse and database architectures: open table formats (e.g. Iceberg), Parquet, object storage, query engines such as Athena/Trino or Redshift, relational dat
- Understanding of partitioning, compaction, schema evolution and query performance
- Built and run batch and event-driven pipelines at TB scale (e.g. Spark, Glue, Step Functions, Airflow or Dagster), including backfills, failure recovery and data quality checks
- Hands-on experience with data catalogs and metadata (e.g. DataHub, OpenMetadata, Glue Data Catalog, Unity Catalog), lineage, data contracts or data products — or strong demonstrable interest in data m
- Works with AI coding agents daily; has built (or is eager to build) LLM agents, MCP servers or tools on top of data systems
- Strong production Python (tested, typed, maintainable) and expert SQL
- DevOps mindset: infrastructure as code, hands-on with AWS, Terraform, containers/Kubernetes, CI/CD and production monitoring
- Technical leadership: drives consensus across teams, explains architectural trade-offs, makes people around them better
Nice to have
- Experience with spatial indexes and tools (e.g. H3, S2, PostGIS) and location time-series data
- Experience in programmatic advertising, audience/segment data or privacy and consent requirements
- Experience building metrics or semantic layers serving self-service analytics and AI-driven data access
Full description
At Adsquare, our mission is driven by our core focus:
- Passion – Solving complex challenges with great people, tech, and data.
- Niche – Location Intelligence for Programmatic Advertisers.
Our core values are integral to everything we do:
- Drive: We turn ambition into action.
- Resilience: We adapt, persevere, and grow stronger.
- No BS: We value honesty, transparency, and clear communication.
- Humble: We choose modesty over vanity and let results speak for themselves.
- Moral Compass: We do the right thing with fairness, integrity, and respect.
We seek candidates who not only bring top-tier technical expertise but also embody these values in every aspect of their work.
We are looking for a Staff Data Platform Engineer to build and own the shared data platform that the Data team and the rest of Adsquare build on: ingestion, lakehouse storage, databases, the data catalog, and the agentic tooling that sits on top of it all.
This is a highly technical, hands-on Individual Contributor (IC) role at the intersection of DevOps and data engineering. You will design data systems and also own how they are deployed, run and kept healthy in production – infrastructure as code, CI/CD, containers, observability and cost. You will be the technical lead for our data platform – making the key architectural calls and setting engineering standards – and you will build the pipelines, design and ship the services. There are no people-management responsibilities.
Our platform processes TB-scale geo-spatial data, audience attributes and location time-series. We are moving towards a data mesh, where domain squads own and publish their data as products, and towards a way of working where much of our engineering is done with and by AI agents. You will shape both.
We are looking for a builder: an engineer with deep platform knowledge who still loves shipping code, and who is excited about how AI agents are changing data engineering.
Must-Have Skills:
- Experience: 7+ years in Data Engineering, Data Platform or Backend Engineering, including significant time at senior or staff level with platform-wide scope – and still hands-on.
- Lakehouse & database design: Deep experience designing and operating lakehouse and database architectures – open table formats (e.g. Iceberg), Parquet, object storage, query engines such as Athena/Trino or Redshift, plus relational databases. You understand partitioning, compaction, schema evolution and query performance.