Senior Data Engineer

Title: Senior Data Engineer

Client: PG&E

Location: Hybrid – Dublin, CA

Duration: 12+ Months

Visa: USC/GC

Rate: $98/hr. W2

TOP THINGS: Experience with data engineering / modelling, interpersonal skills and the ability to explain technical issues to non-technical people, Snowflake / Fabric experience

The Senior Data Engineer will lead data migration efforts to Snowflake, develop complex ETL processes, build and enhance Power BI dashboards, and deliver actionable analytics that drive operational efficiency, identify bottlenecks, and improve customer satisfaction. This is a high-impact, hands-on role requiring advanced technical expertise combined with strong interpersonal skills to translate complex data insights for non-technical business stakeholders.

You will work closely with the Operations Data Analyst Principal and cross-functional teams in a collaborative environment focused on solving complex, high-visibility problems in a highly regulated utility industry.

Key Responsibilities

Conceptualize, design, and build scalable data infrastructure and pipelines that enable efficient access and analysis of large-scale datasets.

Develop and optimize complex SQL queries (thousands of lines of code) to build underlying tables that power reporting and analytics.

Lead data migration and optimization efforts to Snowflake; share expertise with the team on best practices for data modeling and storage in the new environment.

Design, implement, and maintain ETL processes using Python (Spark) for data scrubbing, quality control, transformation, and statistical analytics (e.g., calculating project durations and identifying trends).

Build, modify, and enhance complex Power BI dashboards and reports to provide visibility into project status, stalled jobs, and key performance metrics.

Extract and integrate data from SAP (primary system of record) and other sources.

Partner with business users and project managers to understand requirements, ask the right questions, and translate technical findings into actionable business insights.

Deploy and support machine learning algorithms in production environments where applicable.

Apply software engineering best practices including unit testing, CI/CD, and source control.

Mentor junior team members and provide guidance on complex data and analytics problems.

Communicate recommendations clearly (oral and written) to technical and non-technical audiences.

Support regulatory reporting needs (e.g., CPUC, FERC) with high data quality and accuracy.

Education

BA/BS in Computer Science, Management Information Systems, or related field (or equivalent experience).

Experience & Skills

5+ years of experience in data engineering and ETL ecosystems (Spark, Informatica, SAP BODS, or similar).

Advanced/expert-level SQL programming – ability to write complex, ad-hoc queries by hand on large datasets (tens of millions of records).

Hands-on experience with Snowflake (strong priority for data migration and optimization).

Proficiency with Python for ETL, scripting, and statistical analytics.

Experience with SAP data extraction and integration.

Strong Power BI skills for dashboard development and visualization.

Knowledge of software engineering principles (unit testing, CI/CD, source control).

Experience with machine learning algorithm deployment (or strong statistical analytics background).

Proven ability to explain technical concepts and issues to non-technical stakeholders.

Experience in highly regulated industries (e.g., Banking, Utilities) is highly preferred.

Nice-to-Have

Microsoft Fabric experience.

Background in statistical modeling (e.g., ANOVAs in Excel or Python).

Success Factors

High proficiency in statistical analytics and intuition for "asking the right questions" of business users.

Strong interpersonal and communication skills.

Ability to thrive in a fast-paced, growing organization with evolving data needs.

Passion for solving complicated problems through data and delivering measurable business impact.