Data Engineering Lead (Snowflake) - Bay Area, CA (Hybrid)

The 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.

Role and scope

Titles vary across industry: product owner (PO), project manager, scrum master, TPM; at similar roles may be labeled “product managers.”

Not seeking a pure scrum master or a typical external-facing PO who only writes requirements.

The 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.