Staff Data Platform Engineer (m/f/d)

Job summary

Build and own a shared data platform for ingestion, lakehouse storage, databases, data catalogs, and developer-focused AI agents. Design and operate production systems for terabyte-scale geospatial, audience, and location time-series data, establish data mesh standards, and lead architecture, reliability, observability, and cost management across teams.

Benefits

Qualifications

• At least 7 years of experience in data engineering, data platforms, or backend engineering, including senior- or staff-level platform scope.
• Deep experience designing and operating lakehouse and database architectures, including open table formats, Parquet, object storage, query engines, and relational databases.
• Experience with partitioning, compaction, schema evolution, and query performance.
• Experience building and operating terabyte-scale batch and event-driven pipelines, including backfills, failure recovery, and data quality checks.
• Hands-on experience with data catalogs and metadata, lineage, data contracts, or data products; or demonstrable interest in data mesh backed by adjacent experience.
• Regular use of AI coding agents and experience building, or willingness to build, LLM agents, MCP servers, or tools for data systems.
• Strong production Python and expert SQL skills.
• Hands-on experience with AWS, Terraform, containers or Kubernetes, CI/CD, and production monitoring.
• Ability to build consensus, explain architectural trade-offs, and support the development of other engineers.

Responsibilities

• Design, build, and operate ingestion and processing pipelines, lakehouse storage, query layers, and databases.
• Create a self-service platform for squads to own, publish, and consume data products.
• Establish standards for data contracts, schema evolution, ownership, and production readiness.
• Improve data discovery, documentation, lineage, quality signals, and ownership.
• Build agents, MCP servers, and tools to explore data, validate pipelines, debug incidents, and automate operations.
• Set standards and guardrails for AI-assisted engineering and agent-written code.
• Build monitoring, alerting, and data quality checks; manage cloud costs.
• Lead architecture decisions, conduct design and code reviews, and mentor engineers.

Skills

Industry

Relocation