Data Platform Engineer

📋 Description Own end-to-end real-time data pipeline across the analytics warehouse. Design/build scalable data pipelines with AWS Glue (PySpark). Optimize the ClickHouse warehouse for sub-second queries. Implement data contracts; onboarding a new operator is a config change. Build a feature-serving layer delivering pre-computed features to AI agents. Collaborate with data scientists, BI, and infra teams. 🎯 Requirements 3+ years building and operating production data pipelines. Expertise in Apache Kafka (Amazon MSK). Strong SQL and warehouse engineering (ClickHouse preferred). PySpark/Spark Streaming; AWS Glue, Airflow, NiFi a strong plus. Data modelling for multi-tenant schemas with data contracts governance. CI/CD and infrastructure-as-code (CloudFormation, Terraform, CDK); containers (ECS Fargate or Kubernetes). 🎁 Benefits Fully remote with asynchronous-first communication. EU time zone overlap is preferred. Small, high-autonomy Data team; report to Head of Data. Architecture decisions documented; design reviews; domain ownership. Culture: mature, mission-driven, low-ego.