Data platform engineer for location intelligence

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.

• Design, build and operate our ingestion and processing pipelines, lakehouse, query layer and databases.
• Make clear trade-offs between latency, correctness, cost and long-term maintainability.
• Turn the platform into a self-serve foundation that lets squads own, publish and consume data products.
• Define the standards for data contracts, schema evolution, ownership and production readiness.
• Make our data discoverable, documented and trusted – with lineage, quality signals and clear ownership – so that both people and AI agents can find and use the right data.
• Design and ship agents, MCP servers and tools that let engineers and agents explore data, validate pipelines, debug incidents and automate routine operations.
• Set the team’s standards for agentic coding: how we use coding agents, share skills, review agent‑written code and keep guardrails in place.
• Build monitoring, alerting and data quality checks that catch problems before they reach downstream products, and keep cloud costs visible and under control.
• Drive architecture decisions across squads, raise the bar through design and code reviews, and mentor Senior, Mid and Junior engineers.
• 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.
• 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.
• You have 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, AWS Sagemaker Catalog, Glue Data Catalog, Unity Catalog), lineage, data contracts or data products – or a strong, demonstrable interest in data mesh backed by adjacent experience.
• You work with AI coding agents every day and get real leverage from them, and you have built (or are eager to build) LLM agents, MCP servers or tools on top of data systems.
• Strong production Python (tested, typed, maintainable) and expert SQL.
• A DevOps mindset: you treat infrastructure as code and are hands‑on with AWS, Terraform, containers/Kubernetes, CI/CD and production monitoring.
• You drive consensus across teams, explain architectural trade‑offs clearly to engineers and non‑technical stakeholders, and make the people around you better.
• 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 that serve self‑service analytics and AI‑driven data access.
• A personal learning budget of 1,200 EUR a year
• 30 vacation days a year
• Urban Sports Club membership
• company pension scheme and relocation / home office budget
• Regular team and company events organised by our People team
• Latest hardware and all tools you need to thrive
• Salary Range (Annual On-Target Earnings) 90,000 - 105,000 euros (OTE)