Staff Data Platform Engineer

About the Role As a Staff Data Platform Engineer you will design and evolve data pipeline architecture and storage systems, driving technical direction across the team. Build and deliver high quality data pipelines end to end from initial design through production deployment. Mentor engineers, raise the technical bar through code reviews, and unblock teammates on complex problems. Own team outcomes by setting expectations, ensuring delivery quality, and taking accountability for results.

Requirements 8+ years of hands-on software engineering experience with significant depth in data pipelines, backend services, or data platform engineering Deep experience designing and operating data lakes warehouses lakehouses at production scale Experience in scaling data pipelines and understanding trade-offs (performance resources) Expert Python skills, you write clean, performant, testable code and can establish standards for others Experience across the modern data processing stack e.g., Kafka or Redpanda, Flink or Spark, Airflow or Dagster Expert-level SQL with complex joins, query planning and optimization, and schema design across OLTP and OLAP Strong database architecture skills Solid distributed systems experience Comfortable leading technical discussions and building consensus on architectural decisions Proficiency in English Experience with distributed Clickhouse cluster Blockchain domain knowledge or ability to master complex technical domains quickly Track record of driving engineering standards and best practices across a team No previous knowledge of Blockchain technology required

Responsibilities Design and evolve data pipeline architecture and storage systems, driving technical direction across the team Build and deliver high quality data pipelines end to end from initial design through production deployment Mentor engineers, raise the technical bar through code reviews, and unblock teammates on complex problems Own team outcomes — set expectations, ensure delivery quality, and take accountability for results

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