Data Platform Engineer

About the role

At HelloFresh, data is at the heart of everything we do — from the moment a customer places an order to the way we forecast demand, optimize our supply chain, and personalize experiences for millions of people. Making that data fast, reliable, and available is what our Data Platform makes possible.

We are looking for a Senior Data Platform Engineer to join our Operational Data Platform team — the squad that ensures operational data is created, delivered, and shared downstream reliably, cost-efficiently, and with the quality guarantees that everything downstream depends on — so the analytics layer receives quality data, ready to be turned into governed assets. You will build the streaming, messaging, and self-service provisioning systems that hundreds of backend and data engineers rely on every day.

This is a hands-on engineering role at the core of our platform. You'll own critical infrastructure, drive efficiency, and help define the "golden path" that makes it effortless for engineers across the company to store and stream their data — with governance and cost control built in from the start.

What you'll do

• Build and run our streaming and messaging platform. Own the systems that move data in real time and at scale — Kafka, Kafka Connect, Flink, and SQS — and keep them fast, resilient, and easy to build on.
• Drive efficiency. Identify and act on opportunities to reduce the cost and complexity of the platform, and make efficiency a default rather than an afterthought.
• Own the reliability of critical data paths. Keep the systems at the heart of the platform highly available, and continuously improve their resilience, observability, and operational maturity.
• Enable self-service for operational data stores. Build and maintain the Terraform modules and tooling that let engineering teams use the right database for their use case within minutes, with governance and cost guardrails out of the box.
• Build AI-powered self-service. Develop tooling — including AI and agent-based capabilities — that lets teams operate and maintain their own data infrastructure, so the platform runs without us in the loop.
• Raise the bar on data quality for operational data, including data quality checks on Kafka, so downstream analytics can trust the data from the moment it's created.
• Collaborate across the platform. Work closely with the Analytical Data team so high-quality operational data flows seamlessly into the analytics platform through clean, well-defined handover points.