platform engineer for AI data workflows

DeepL is a global AI product and research company focused on secure, intelligent solutions for complex business problems. Its Language AI platform provides human-like translation, improved writing, and real-time voice translation for individuals and businesses worldwide.

• Build and evolve data platform infrastructure, including the Databricks-based lakehouse, Kafka consumers, and foundational tooling for data engineers;
• Support and extend dlt to make data ingestion patterns reusable and robust;
• Make technical decisions that enable the platform to scale with DeepL’s data volume and use-case diversity;
• Build connectors, interfaces, and integrations that bring data to humans and AI agents, including MCP connectors and workflow skills;
• Design AI-powered data workflows for data engineers, analysts, business teams, and AI tools;
• Implement data observability, quality frameworks, monitoring, and alerting;
• Own infrastructure-as-code, CI/CD for data workflows, access management, security configurations, audit trails, and spend governance;
• Build golden-path templates and patterns that help engineers across the company use data safely and efficiently.

• Hands-on experience building and operating cloud-based data infrastructure;
• Experience with Terraform/Terragrunt, CI/CD for data workflows, and Docker/Kubernetes;
• Production-quality Python proficiency;
• Reliability mindset, including observability, meaningful alerts, production ownership, and incident-driven improvements;
• Platform-product mindset focused on developer experience and reducing friction for platform users;
• Communicates effectively across different audiences and actively uses feedback from data consumers;
• Actively uses AI-powered tools to move faster and focus on architecture, system design, and scalability tradeoffs;
• Nice to have: experience with Databricks, Apache Iceberg, Kafka, or similar lakehouse and streaming technologies.

• Hybrid work schedule with office attendance twice a week and flexible working hours;
• Virtual Shares for every employee;
• Regular in-person team events;
• Monthly full-day hacking sessions;
• 30 Days of annual leave excluding public holidays;
• Mental health resources;
• Competitive benefits tailored to the employee’s location.