Related skills
aws airflow kafka spark iceberg📋 Description
- Lead data org through directors/managers; evolve data engineering & platform architecture.
- Architect and scale distributed systems for petabyte-scale data & billions of events.
- Collaborate cross-functionally to drive data vision and operating model aligned with corporate goals.
- Obsess over developer experience; build self-service capabilities to speed delivery.
- Manage platform performance and cost; adopt open-source tools such as Airflow, Debezium, Iceberg, Trino, Spark.
- Mentor international engineering teams; set frameworks for technical excellence and rigor.
🎯 Requirements
- Scale Systems Expertise: large-scale distributed data platforms on cloud (AWS preferred).
- Platform-First Mindset: build internal developer frameworks, not just pipelines.
- Technical Depth: strong software engineering and distributed systems (batch & real-time).
- Global Leadership: lead and scale international teams of 50+ engineers.
- Open-Source Fluency: familiarity with Airflow, Debezium, Kafka, Spark, Clickhouse.
- Data Fanaticism: use data to improve performance, cost and velocity.
🎁 Benefits
- Project Execution: Open-source, scalable, self-service environment adopted company-wide.
- System Impact: Improvements in latency, throughput, and cost-efficiency.
- Team Impact: Increase developer velocity by removing friction and AI tool support.
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