• Designing and maintaining scalable data pipelines for ingestion, transformation, and delivery across multiple data sources • Collaborating with Analytics Engineers and Product teams to curate datasets and establish data contracts that improve transparency and reliability • Developing and managing modern data architectures, such as lakehouses and medallion layers, using tools like Databricks, Delta Lake, or Iceberg • Optimizing Snowflake usage and performance, ensuring data quality and cost efficiency • Supporting and scaling orchestration platforms (like Dagster), metadata systems (like Unity Catalog or Collibra), and monitoring tools (like Datadog) • Collaborating with data engineering, analytics engineering, and security teams to deliver stable and efficient infrastructure for diverse workflows • Building tools, alerting systems, and documentation that ensure reliable operation and developer self-service across our data stack