Data Engineering Leader

Core technical expectations: • Strong data ecosystem background: experience leading data products or data warehousing initiatives. • Solid understanding of schemas, databases, and ETL (Extract, Transform, Load) processes; no hands-on coding expected but must be able to engage deeply with engineers and "know what they are talking about.” • Primary data warehouse platform: Snowflake. • Broader big data background acceptable if not purely Snowflake (e.g., Databricks, BigQuery, Redshift). • Current ETL tool: Informatica; hands-on Informatica expertise is not required. • Analytics/visualization not in scope; Power BI knowledge is a nice-to-have, not mandatory. Role and scope: • Titles vary across industry: product owner (PO), project manager, scrum master, TPM; at PG&E, similar roles may be labeled "product managers.” • Not seeking a pure scrum master or a typical external-facing PO who only writes requirements. • Role must interface with both business and engineers; expected to work directly with engineering teams. • Focus is on the enterprise data platform and data engineering; not an analytics/visualization role. Core technical expectations • Strong data ecosystem background: experience leading data products or data warehousing initiatives. • Solid understanding of schemas, databases, and ETL (Extract, Transform, Load) processes; no hands-on coding expected but must be able to engage deeply with engineers and "know what they are talking about.” • Primary data warehouse platform: Snowflake. • Broader big data background acceptable if not purely Snowflake (e.g., Databricks, BigQuery, Redshift). • Current ETL tool: Informatica; hands-on Informatica expertise is not required. • Analytics/visualization not in scope; Power BI knowledge is a nice-to-have, not mandatory.