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Data Engineer II, Operations

Delivery Hero — Germany · Posted ~1 hour ago

Mid Full-time Visa History ✓

Skills

Data engineering Data pipelines Software architecture Pipeline maintenance Test-driven development CI/CD Engineering best practices TDD

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Summary ✨ AI‑Generated

Join an international engineering team as a Data Engineer II focused on improving operational and supply-chain workflows through data engineering. You will develop valuable features, maintain reliable data pipelines, contribute to scalable architecture, and promote strong engineering practices such as TDD and CI/CD. The role combines hands-on engineering with meaningful operational impact in a high-scale environment.

Highlights

Work with an international and experienced engineering team on scalable, reliable operational systems serving a large customer base. The role offers opportunities to shape architecture, improve engineering practices, and deliver meaningful operational value.

Description

Job DescriptionWe are looking for a skilled Data Engineer II to join our team and help us take our operations to the next level. The team's mission is to improve vendors' experience and bring value to the critical path of supply chain process through data science and data engineering. You will be working with an international and experienced team, shaping the experience for millions of customers who order daily through our platform. You’ll help design, build, and maintain the features and workflows that enable scalable and reliable rollouts. You'll drive engineering excellence and collaborate closely with our fellow colleagues. Join us in building and maintaining this mission-critical service! Key Responsibilities Develop features that bring value to our users Pipeline Maintenance to ensure our product runs smoothly Play an active role in evolving our overall architecture, establishing best engineering practices within the team (e.g. TDD, CI/CD, etc.) to improve the speed of delivery, and the quality of the features and services you own. Collaborate with data scientists and data engineers to optimize model lifecycle, monitoring, and alerting. Develop and maintain CI/CD pipelines for ML models.