Data platform engineer in adtech

Adsquare company; Berlin; On-site; EUR 90,000 - 105,000; Full time

Job summary

Adsquare is seeking a Staff Data Platform Engineer to 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 hands-on IC role at the intersection of DevOps and data engineering.

Design, build and operate ingestion and processing pipelines, lakehouse and query layer; define data contracts, schema evolution and production readiness.

Qualifications

• 7+ years in Data Engineering or Backend with platform-wide scope and hands-on work.
• Deep experience designing lakehouse and database architectures (Iceberg, Parquet, object storage).
• TB-scale batch and streaming pipelines (Spark, Airflow, Dagster) with backfills and quality checks.
• Data catalogs and metadata experience; lineage, contracts or data products.
• Strong Python (typed) and SQL; DevOps mindset with IaC and AWS.

Responsibilities

• Design, build and operate ingestion and processing pipelines, lakehouse, query layer and databases.
• Turn platform into a self-serve foundation for squads to publish and consume data products.
• Define standards for data contracts, schema evolution, ownership and production readiness.
• Make data discoverable and trusted with lineage, quality signals and ownership.
• Design and ship agents, MCP servers and tooling to explore data and automate operations.
• Set coding agent guardrails and review agent-written code; mentor engineers.
• Build monitoring, alerts and data quality checks; manage cloud costs.
• Drive architecture decisions and mentor Senior, Mid and Junior engineers.

Skills

Data platform design

Python

SQL

AWS

Terraform

Kubernetes

DevOps mindset

Data governance

Tools

Iceberg

Parquet

DataHub

Glue Data Catalog

OpenMetadata

OpenMetadata

Athena/Trino

S3

Job description

Описание:

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.

Задачи:

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.

Требования:

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.

Будет плюсом: 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

Условия:

90,000 - 105,000 euros (OTE)