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DeepL is seeking a Senior Data Platform Engineer to join its Data Platform team in London. The role focuses on building and operating the infrastructure that powers DeepL's Language AI platform, which serves over 100 million users and 200,000+ business customers globally.
Key responsibilities include:
- Build and evolve core data platform infrastructure: design and advance the Databricks-based lakehouse, Kafka consumers for reliable data ingestion at scale, and foundational layers that data engineers build workflows on top of. Support and extend tooling like dlt (data load tool) to make ingestion patterns reusable and robust.
- Enable AI-powered data workflows: develop connectors, interfaces, and integrations (MCP connectors, workflow skills) that bring data to humans and AI agents. Design for diverse users including data engineers, analysts, business teams, and AI tools.
- Ensure data trustworthy at scale: implement data observability, quality frameworks, monitoring, and alerting systems that give data consumers confidence and provide visibility to catch problems early.
- Steward infrastructure, developer experience, and governance: own infrastructure-as-code (Terraform/Terragrunt), CI/CD for data workflows, access management, security, audit trails, and spend governance. Build golden-path templates and patterns for safe, fast data access across the company.
Required qualifications:
- Hands-on experience building and operating cloud-based data infrastructure
- Proficiency with infrastructure-as-code, CI/CD, and container technologies (Docker/Kubernetes)
- Production-quality Python coding skills (primary language for the team)
- Strong reliability mindset: builds for observability, writes meaningful alerts, owns production systems
- Platform-product mindset: treats engineers and analysts as primary users, focuses on developer experience
Expected:
- Clear cross-functional communication across different audiences
- AI-native velocity: actively uses AI-powered tools to move faster and tackle harder problems
Nice-to-have:
- Experience with Databricks, Apache Iceberg, Kafka, or similar lakehouse/streaming technologies
- Familiarity with Go or Java
