Design and build scalable data solutions spanning ingestion, modelling, pipelines, and platform infrastructure. Own complex technical problems, improve data quality and self-service capabilities, and operate production systems with monitoring and incident response. Use Snowflake, dbt, Prefect, AWS, Terraform, and Flink to develop reliable data platforms and real-time products. Collaborate with product, security, engineering, and data-consuming teams while promoting automation, testing, CI/CD, and modern engineering practices.

Lead data and AI governance initiatives by evolving governance frameworks, creating practical guidance, delivering literacy programs, and partnering with technical, privacy, regulatory, risk, and business teams. The role focuses on responsible AI adoption, data stewardship, quality, lineage, transparency, explainability, bias mitigation, regulatory alignment, and translating policy into scalable technical and operational practices.

Lead a distributed data engineering team to design, build, and maintain core data models and real-time data flows on an AWS/Snowflake platform. Balance strategic architecture and hands-on delivery, manage risks and dependencies, establish SLOs and DataOps practices, and coach senior engineers to improve platform quality and performance.