VeeAR Projects Inc. Verified
Construction, Infrastructure
Data Engineering Leader
Oakland, California, United StatesOnsiteContractPosted 2 months agoVisa sponsorship available
Role summary
This role is for a Data Engineering Leader responsible for the enterprise data platform and data warehousing initiatives. The leader will interface with both business stakeholders and engineering teams, ensuring a deep understanding of data schemas, databases, and ETL processes. While hands-on coding is not expected, a strong grasp of data ecosystem concepts is crucial. Experience with platforms like Snowflake, Databricks, BigQuery, or Redshift is required, along with familiarity with ETL tools such as Informatica. This is not an analytics or pure scrum master role, but rather a leadership position focused on driving data engineering outcomes.
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.
