Data Engineer, Operations Technology (all genders)

HelloFresh is a global technology company with a team called HelloTech that builds the digital products powering a subscription-based food experience, including meal kits, ready-to-eat meals, pet food, and premium meat & seafood. The Supply Chain Data Engineering team focuses on harmonizing supply chain data to enable data-driven decision making across menu planning, procurement, fulfillment, and logistics, powering operational processes and telemetry globally.

• Hands-on experience working with AI tooling (e.g., Claude Code, Cursor, Copilot) beyond casual experimentation.
• Proven scientific or engineering work (Bachelor's, Master's, or PhD) in computer science, software engineering, or related field.
• 3+ years of work experience as a Data Engineer including delivery of production data.
• Fluency in Python, SQL, and PySpark for building scalable ETL/ELT data pipelines on modern cloud data infrastructure.
• Strong data modeling expertise (dimensional modeling, relational architecture, event-driven data streams) applied to supply chain or logistics operations.
• Experience with software development practices and tools such as Git, CI/CD, Docker, and AWS.
• Exceptional communication skills to bridge technical details with warehouse operators, logistics planners, and business stakeholders.
• Strong ownership and bias for shipping quality work.
• Product sense with the ability to support opinions with data and user evidence.

• Become an integral part of a high-impact engineering team supporting global supply chain, procurement, and logistics operations.
• Design, build, and maintain robust batch and streaming data pipelines connecting procurement systems, warehouse management systems (WMS), and logistics networks.
• Model complex supply chain domains—including recipe component sourcing, inventory turnover, fulfillment batching, and route optimization—into clean, scalable analytical datasets.
• Develop real-time data integrations for tracking ingredient inventory levels, order assembly status, and carrier shipment tracking across distribution centers.
• Partner with Data Scientists and Operations Analysts to operationalize demand forecasting models, waste reduction algorithms, and safety stock optimizations.
• Ensure high data quality, freshness, and lineage tracking for operational dashboards, executive KPIs, and automated logistics alerts.
• Work with modern cloud data technologies such as AWS (S3, EMR, Glue, Redshift), Apache Spark/PySpark, Kafka, Airflow, Snowflake, and Databricks.
• Collaborate closely with cross-functional stakeholders in Procurement, Fulfillment Operations, Logistics, and Product to turn physical workflow requirements into data infrastructure.
• Contribute to a collaborative and knowledge-sharing environment, providing technical guidance and coaching to team members and stakeholders.
• Operate what you build by instrumenting, monitoring, and improving your systems in production.