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Job Description
MEET DEEPL
DeepL is a global AI product and research company focused on building secure, intelligent solutions to complex business problems. Over 200,000 business customers and millions of individuals across 228 global markets today trust DeepL's Language AI platform for human-like translation, improved writing and real-time voice translation.
Founded in 2017 by CEO Jaroslaw “Jarek” Kutylowski, DeepL now has around 1,000 passionate employees and is supported by world-renowned investors including Benchmark, IVP, and Index Ventures.
Our goal is to become the global leader in trusted, intelligent AI technology, building products that drive better communication, foster connections, and create a meaningful impact. To achieve this, we need talented people like you to join our journey. If you’re ready to shape the future of AI and grow your career in a fast-moving, purpose-driven environment, DeepL is your next destination.
WHAT SETS US APART
What sets us apart is our blend of cutting-edge AI technology, meaningful work, and a culture where people truly thrive. We’re a team of innovators, researchers, and creators driven by a shared purpose to unlock human potential by making work simpler, smarter, and more connected.
When we share what it’s like to work at DeepL, the reactions are overwhelmingly positive. This might be because of our technology that helps millions of people and businesses communicate and work better every day, or because of the trust, curiosity, and care that shape our culture.
What we know for sure is this: being part of DeepL means joining a team dedicated to innovation, growth, and well-being. Discover more about life at DeepL onLinkedIn https://www.linkedin.com/company/deepl/,Instagram https://www.instagram.com/deepl_official/, and our Blog https://www.deepl.com/en/blog.
MEET THE TEAM BEHIND THIS JOURNEY
DeepL's Language AI reaches over 100 million users, but the decisions behind every model improvement, every product launch, and every business milestone run on data. The Data Platform team is the engineering foundation that makes that possible.
We build and operate the infrastructure that the entire company relies on to work with data effectively — ingestion infrastructure, a reliable lakehouse, the tooling that data engineers build on top of, and increasingly, AI-powered interfaces (MCP connectors, workflow skills, and integrations) that bring data directly into how people and AI agents get work done across DeepL. Our customers aren't just data teams; they're the whole company.
We're looking for engineers who care as much about the experience of the people who use their systems as they do about the quality of the systems themselves, who take responsibility from architecture to production, and who find meaning in work whose impact compounds quietly across an entire organization. If that resonates, this is your team.
YOUR RESPONSIBILITIES
- Build and evolve the data platform infrastructure: shape and advance the core infrastructure our data ecosystem runs on — our Databricks-based lakehouse, Kafka consumers that reliably ingest data at scale, and the foundational layer that data engineers build their workflows on top of. You'll also support and extend tooling like dlt (data load tool) to make ingestion patterns reusable and robust, and make technical decisions that let the platform grow with DeepL's data volume, use-case diversity, and scale
- Enable AI-powered data workflows: build the connectors, interfaces, and integrations that bring data into the hands of humans and AI agents alike, including MCP connectors and workflow skills that let the rest of DeepL access and work with data in AI-assisted workflows. Design for the full range of users — data engineers, analysts, business teams, and the AI tools they use every day
- Make data trustworthy at scale: build the systems that make data reliable, not just available. Implement data observability, quality frameworks, monitoring and alerting that give every data consumer confidence in what they work with, and give the team visibility to catch problems before they become incidents
- Steward infrastructure, developer experience, and governance: take responsibility for how the platform is built and operated — infrastructure-as-code (Terraform/Terragrunt), CI/CD for data workflows, access management, security configurations, audit trails, and spend governance. Build the golden-path templates and patterns that make it fast and safe for engineers across the company to get value from data
QUALITIES WE LOOK FOR
Must-have
- Cloud data infrastructure experience — solid, hands-on experience building and operating cloud-based data infrastructure; comfortable with infrastructure-as-code (Terraform/Terragrunt), CI/CD for data workflows, and container technologies (Docker/Kubernetes)
- Python proficiency — writes production-quality Python code. Python is our primary language on the Data Platform; familiarity with Go or Java is a plus but not required
- Reliability and operational excellence — brings a reliability mindset to data: builds for observability, writes meaningful alerts, owns systems in production, and turns incidents into durable improvements
- A platform-product mindset — treats the engineers, analysts, and teams who build on the platform as primary users; thinks deeply about developer experience and reduces friction proactively
Expected
- Clear, cross-functional communication — communicates effectively across different audiences, actively seeks feedback from data consumers, and uses that input to improve the platform
- AI-native velocity — actively uses AI-powered tools to move faster and take on harder problems, freeing focus for the decisions that matter: architecture, system design, and the tradeoffs that determine whether a platform scales gracefully
Nice-to-have
- Lakehouse and streaming technologies — experience with Databricks, Apache Iceberg, Kafka, or similar is a stro…
AI Stack
Skills Required
RAG
Research
Data + AI
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