> Markdown version of [/jobs/ext/4500027-data-platform-engineer](https://www.wearedevelopers.com/jobs/ext/4500027-data-platform-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Platform Engineer

- **Company:** Trade Republic
- **Location:** Berlin, Germany
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Data Analysis, Data Infrastructure, Data Systems, Python (Programming Language), Systems Integration, ReactJS, Grafana, Apache Spark, Backend, Kubernetes, Nintex, Data Management, Front End Software Development
- **Published:** October 31, 2026
- **Apply:** https://www.adzuna.de/details/5947070477

## About the Role

* 3+ years building backend or platform services
 * A solid understanding of how data platforms work (query engines, orchestration, lakehouse storage). You build on top of the infrastructure rather than run it.
 * Demonstrated ability to turn best practices into opinionated "paved roads" that make doing the right thing effortless.
 * Clear, concise English communication.
 * Nice to have: React and frontend experience.

The toolbox we use (and you probably know): Python, Spark, Kyuubi, Iceberg, Airflow, dbt, n8n, Kubernetes, AWS, Grafana. Experience with every single item is not required-bring your strengths and curiosity.

## Description

Trade Republic is known for shipping fast and strong, and at the core of this is the Data Platform: making every employee and every system self-serve with data. As part of Data Systems, you'll build the analytics platform people across the company rely on every day. The aim is minimum cognitive load and maximum business value for hundreds of data consumers.

 * Build the data platform: Build and evolve the data systems data users love. That includes our query experience, conversational analytics, dashboarding, integrations with tools like n8n, and the Airflow orchestration layer. Design simple interfaces that hide the complexity of the data platform underneath.
 * Engineer for resilience at scale: Critical systems and hundreds of consumers depend on the analytical plane, so every change you ship is tested, rolled out safely and observable. Define and monitor SLOs and error budgets for customer-facing services. Lead blameless post-incident reviews and automate safety guardrails.
 * Own the data platform: Shape the roadmap end-to-end. Work with product managers to understand user needs, balance cost, latency and user experience, pick the right tech, and clearly explain trade-offs to leadership.