Hybrid Data Engineer: ETL, Snowflake & Cloud Solutions

Pacific Gas and Electric; Oakland (CA); Hybrid; USD 102,000 - 162,000; Full time

Job summary

Talentify is seeking a data engineer in Oakland for designing, developing, and optimizing data extraction, transformation, and loading processes across sources. You will collect metadata, manage data lineage, and work with stakeholders through the development lifecycle in a hybrid setting with 1–2 days onsite.

The role emphasizes data integration, big data tooling, and cloud platforms. Collaboration with business teams and leadership is expected to deliver scalable data solutions.

Qualifications

• Bachelor's degree in Computer Science or related discipline or equivalent experience.
• 3 years of experience with data engineering/ETL ecosystems (e.g., Informatica, SAP BODS, OBIEE).

Responsibilities

• Analyzes existing applications and systems and formulates logic for new systems, devises logic procedures, logical database design, performs coding and tests/debugs programs.
• Designs and deploys new systems and enhancements to existing systems ensuring compatibility and inter-operability.
• Works on moderately complex problems that require in depth analysis and judgment to obtain results or solutions.
• Resolves application problems within procedural guidelines.
• Provides technology that supports solutions which meet business capabilities and are consistent with enterprise standards, architectures and strategies.

Skills

Python

PySpark

SQL

Snowflake SQL

Education

Bachelor's degree in CS or related field

Tools

Informatica

SAP BODS

OBIEE

AWS

GitHub Actions

Jenkins

Terraform

Git

Snowflake Data Cloud

Job description

Talentify is seeking a data engineer in Oakland for designing, developing, and optimizing data extraction, transformation, and loading processes across sources. You will collect metadata, manage data lineage, and work with stakeholders through the development lifecycle in a hybrid setting with 1–2 days onsite.

The role emphasizes data integration, big data tooling, and cloud platforms. Collaboration with business teams and leadership is expected to deliver scalable data solutions.