Enexus Global Inc.
Engineering Technical Lead
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Engineering Technical Lead with a contract length of "unknown," offering a pay rate of "unknown." Located in the Bay Area, it requires strong data ecosystem experience, knowledge of Snowflake, ETL processes, and the ability to interface with engineering teams.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
March 19, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
San Francisco Bay Area
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🧠 - Skills detailed
#Informatica #Snowflake #"ETL (Extract #Transform #Load)" #Data Engineering #Big Data #Microsoft Power BI #Data Warehouse #BigQuery #Databricks #Redshift #BI (Business Intelligence) #Visualization #Databases #Scrum
Role description
Local to Bay area
1 day onsite @ Oakland office.
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 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.
Local to Bay area
1 day onsite @ Oakland office.
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 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.
