Turn business needs into data products: Partner with product managers, analysts, and data scientists to shape requirements and turn them into reusable schemas and data contracts, well-modeled tables, shared metric definitions, and documentation, including lineage, so that people and AI tools can run their own queries and build their own dashboards. Experience building and operating large-scale data pipelines, including orchestration, incremental batch loads, and streaming, using distributed processing or query engines (e.g., Spark, Trino, EMR) on cloud infrastructure (e.g., AWS), with data quality checks, testing, and monitoring built in.