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Jobs(31,361)/Platform Engineer Role(444)/DeepL (28) - Senior Data Platform Engineer
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DeepL

DeepL - Senior Data Platform Engineer

London2d ago
In OfficeSeniorEMEAData AnalyticsPlatform EngineerSenior Data EngineerGoJavaPythonKafkaDatabricksTerraformDockerKubernetesGovernance

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 • 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 • 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 • Lakehouse and streaming technologies — experience with Databricks, Apache Iceberg, Kafka, or similar is a strong advantage

Benefits

• Diverse and internationally distributed team: joining our team means becoming part of a large, global community with people of more than 90 nationalities. We're more than just colleagues; we're a group of professionals with a shared mission to connect diverse cultures. Our global presence is growing–we've doubled in size nearly every year, with our employees based in the UK, Germany, the Netherlands, Poland, the US, and Japan, and we continue to expand our network. • Open communication, regular feedback: as a language-focused company, we value the importance of clear, honest communication. We value smooth collaboration, direct and actionable feedback, and believe that leading with empathy and growth mindset makes us better together. • Hybrid work, flexible hours: we offer a hybrid work schedule, with team members coming into the office twice a week. This allows you to engage directly with your team and experience the unique energy of our workspace, while still enjoying the flexibility and comfort of working from home. With flexible working hours and trust in your productivity, we are in sync with your team’s general locations and time zones to foster effective and seamless collaboration. • Virtual Shares - An ownership mindset in every role. We believe everyone should share in our success, and that’s why every employee receives Virtual Shares, linking your contribution directly to DeepL’s growth and rewarding you with a stake in our future. • Regular in-person team events: we bond over vibrant events that are as unique as our team, from local team and business unit gatherings, to new-joiner onboardings, to company-wide events that bring us all together–literally.

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