Lead the data organization through directors and managers, focusing on the strategic evolution of data engineering and platform architecture.
Architect and scale distributed systems capable of processing petabyte-scale datasets and hundreds of billions of events.
Collaborate with cross-functional teams to drive a company-wide data vision and operating model aligned with corporate goals.
Obsess over the "developer experience," building self-service capabilities and abstractions that reduce time-to-delivery from days to minutes.
Manage the performance and cost efficiency of the platform, including transitions toward open-source technologies like Airflow, Debezium, Iceberg, Trino, and Spark.
Mentor international engineering teams, establishing high-level frameworks for technical excellence and operational rigor.

Scale Systems Expertise: Deep experience architecting and operating large-scale distributed data platforms at a multi-petabyte scale on cloud services (AWS preferred).
Platform-First Mindset: Proven ability to build internal developer frameworks and abstractions rather than just managing pipelines.
Technical Depth: Strong background in software engineering and distributed systems design, specifically with batch and real-time processing.
Global Leadership: Experience leading and scaling international engineering organizations of 50+ professionals.
Open-Source Fluency: Familiarity with modern open-source stacks (e.g., Airflow, Debezium, Kafka, Spark, Clickhouse) and the trade-offs involved in platform architecture.
Data Fanaticism: A relentless focus on using data to improve system performance, cost-efficiency, and developer velocity.

VP of Data Platform – Architecture

Key skills