Senior Data Platform Engineer

In this role you will help build and scale DeepL’s data platform, enabling AI-powered data workflows and trustworthy data at scale. You’ll shape the Databricks-based lakehouse, ingestion pipelines, and tooling to support data engineers, analysts, and AI agents across the company. You’ll drive reliability, observability, and governance while improving developer experience. This is a hands-on, cross-functional role with impact across the organization and a strong emphasis on collaboration and growth.

• Hybrid work with flexible hours
• 30 days of annual leave
• Virtual Shares ownership
• Regular in-person team events
• Hack Fridays monthly
• Competitive location-based benefits

• Build and evolve the data platform infrastructure, including the Databricks-based lakehouse, scalable data ingestion, and foundational tooling for data engineers.
• Enable AI-powered data workflows by creating connectors and interfaces (MCP connectors, workflow skills) for humans and AI agents.
• Ensure data reliability at scale with observability, quality frameworks, monitoring, and proactive incident prevention.
• Own infrastructure, developer experience, governance (IaC with Terraform/Terragrunt, CI/CD for data workflows, access control, security, audit trails, spend governance).
• Create golden-path templates and patterns to accelerate safe data value across the company.

• Cloud data infrastructure experience (IaC, CI/CD for data workflows, containers)
• Production-quality Python coding (Go/Java a plus)
• Reliability mindset with observability and incident handling
• Platform-product mindset focusing on developer experience and reducing friction

• Clear cross-functional communication
• Data consumer-centric mindset
• Proactive collaboration and feedback integration
• Databricks
• Apache Kafka
• Data load tooling (dlt)