Data Engineer

About the Role As a Data Engineer on our ML-scale data infrastructure team, you’ll build and maintain the infrastructure that enables data scientists to move fast and deploy experiments at massive scale. You’ll collaborate with analytics and engineering teams to support real-time features and ML workflows used to optimize rewards and advertiser ROI.

What You'll Do

• Build and maintain the Feature Store, data pipelines, data quality systems, and the data architecture that data scientists depend on
• Translate Data Science requirements into high-performance streams using Apache Flink for stateful processing and real-time feature computation
• Identify and eliminate bottlenecks in ETL and streaming pipelines (Kafka, batch and real-time)
• Design multi-layer data architectures using dbt; reason about Data Lakehouse models and Medallion Architecture
• Collaborate with Data Scientists and Backend Engineers to productionize experiments and ensure low-latency online ML systems
• Implement data validation, monitoring, governance, and security practices; leverage Airflow, Kubeflow, AWS, Terraform, and Kubernetes

What We're Looking For

• 5+ years of data engineering experience on modern stack handling multi-terabyte/day data and thousands of events/second
• Deep hands-on experience with Apache Flink (stateful stream processing) and real-time feature computation
• Strong Java; Go or Python a plus
• Experience optimizing ETL pipelines and real-time systems (Kafka)
• Design experience with dbt, Data Lakehouse concepts, and Medallion Architecture
• Experience working with online ML systems and production-ready experimentation
• Experience with Airflow, Kubeflow, AWS, Terraform, Kubernetes (a strong plus)
• Commitment to data quality, validation, monitoring, governance in production

Nice to Have

• Familiarity with Medallion Architecture
• Additional programming languages (Go, Python) beyond Java

Compensation & Benefits

• Relocation support to Hamburg, Germany; ability to relocate and work remotely from anywhere in the world
• Global, diverse team with talent worldwide; collaboration across 40+ countries
• Systems reaching hundreds of millions of users and billions of decisions daily
• Fast-paced, collaborative environment with opportunities to ship solutions multiple times a day