Pacific Gas and Electric Data Engineer interview questions & guide 2026

The following questions are representative of what candidates face during the Pacific Gas and Electric selection process. These questions, compiled from real reported interview experiences, are designed to test your core technical capabilities, architectural thinking, and alignment with the company's operational values.

SQL & Python Coding

These questions evaluate your hands-on coding ability, data manipulation skills, and your capacity to write clean, optimized code under time constraints.

• Write a SQL query to find the second-highest energy consumption record for a specific utility grid sector.
• Given a dataset of smart meter readings, write a Python script to identify and clean duplicate timestamps and handle missing load values.

Preparing for an interview at Pacific Gas and Electric requires a balanced approach that demonstrates deep technical expertise alongside strong communication skills and safety-focused values.

Role-Related Knowledge – You must demonstrate a strong command of core data engineering tools, specifically SQL, Python, AWS, and Snowflake. Be ready to explain how these technologies function under the hood and how to leverage them to build scalable, fault-tolerant pipelines.

Problem-Solving & Architecture – Interviewers want to see how you approach ambiguous, real-world data challenges. You should be prepared to walk through your design choices step-by-step, explaining the trade-offs between cost, performance, security, and complexity.

Communication & Presentation – Because Data Engineers at PG&E work closely with diverse business units, the ability to translate complex technical concepts into clear, actionable business insights is highly valued. You will need to demonstrate this during your project presentation.

Utility Industry Alignment – Showing an understanding of the unique challenges of the utility sector—such as data privacy, regulatory compliance, and the critical importance of grid safety—can set you apart from other candidates.

The interview process at Pacific Gas and Electric is structured to evaluate both your technical proficiency and your behavioral alignment with the company’s mission. Candidates generally report a professional, structured, and respectful experience, though the timeline between stages can sometimes be lengthy.

The journey typically begins with an online application, followed by a preliminary recruiter phone screen to verify your basic qualifications, education, and career background. From there, the process transitions into automated assessments and live technical evaluations, culminating in a final panel interview.

This visual timeline illustrates the typical progression from the initial application to the final decision. Candidates should prepare for a thorough evaluation that balances automated screening with deep, live technical discussions and presentations. Because the gaps between steps can span several weeks, maintaining a structured preparation routine throughout the process is highly recommended.

To succeed at PG&E, you must perform well across several distinct evaluation areas. Understanding what is expected in each phase will help you focus your preparation effectively.

Live Coding (SQL & Python)

The live technical round evaluates your ability to write clean, efficient, and bug-free code in real time. You will be asked to solve practical data manipulation challenges using SQL and Python.

Be ready to go over:

• SQL Joins and Aggregations – Combining multiple tables, handling null values, and aggregating data across different dimensions.

As a Data Engineer at Pacific Gas and Electric, your daily responsibilities will center around building and maintaining the data foundation that supports the utility's modern enterprise solutions.

You will design, develop, test, and deploy automated data pipelines that ingest structured, semi-structured, and unstructured data from a wide variety of source systems. This includes working closely with business groups to understand their data requirements and translating those needs into reliable data models and ETL workflows.

Collaboration is a core part of the role. You will work alongside data scientists to prepare feature stores for machine learning models, partner with business analysts to build performant reporting layers in tools like the Power Platform (such as Power BI), and coordinate with IT security teams to ensure all data assets comply with strict utility regulations and data governance standards.

Additionally, you will be responsible for monitoring pipeline health, troubleshooting production issues, and continuously optimizing cloud infrastructure to ensure high availability, data integrity, and optimal compute spend.

To be highly competitive for a Data Engineer position at PG&E, you should possess a strong blend of technical expertise, practical experience, and collaborative skills.

Technical Skills

• SQL – Expert-level proficiency in writing complex, highly optimized queries, window functions, and database tuning.
• Python – Strong scripting capabilities for data manipulation, cleaning, and pipeline automation.
• Cloud Platforms – Hands-on experience with AWS services (such as S3, Lambda, Glue, Athena) and modern cloud data warehouses like Snowflake.
• ETL/ELT Design – Deep understanding of data integration patterns, pipeline orchestration tools, and data modeling concepts.
• Power Platform & Analytics – Familiarity with enterprise analytical suites, data visualization tools, and low-code integration platforms is highly valued, particularly for roles aligned with enterprise solutions.

Experience & Soft Skills

• Professional Experience – Typically requires several years of experience in data engineering, data architecture, or a closely related quantitative field, with senior or expert roles requiring extensive track records of leading complex projects.
• Communication – Outstanding ability to present technical architectures and project outcomes clearly to both technical and non-technical audiences.
• Problem-Solving – A structured, analytical approach to diagnosing data issues and designing robust, scalable solutions.
• Must-have qualifications – Solid foundation in computer science or a related field, combined with demonstrated experience building production-grade ETL pipelines in a cloud environment.
• Nice-to-have qualifications – Prior experience in the energy or utility sector, experience with GIS data, or certifications in AWS or Snowflake.

Q: How technical is the interview process for Data Engineers at PG&E? A: The process is thoroughly technical but highly practical. You will face live coding assessments in SQL and Python, scenario-based architecture questions, and a detailed technical presentation. The focus is on your ability to apply your skills to real-world data pipeline and warehousing challenges rather than solving abstract algorithmic puzzles.

Q: What is the format of the technical presentation? A: You will be asked to prepare a 10-minute presentation on a technical project of your choice. This is typically delivered to a panel of engineers and hiring managers, followed by a Q&A session. You should focus on explaining the architecture, your specific technical contributions, the trade-offs you made, and the overall business impact of the project.

Q: How long does the entire hiring process take? A: While the individual interview steps are highly structured and professional, candidates often report that the gaps between rounds can be quite long. It is not uncommon for the entire process, from application to offer, to take several weeks to a couple of months.

Q: Is there a hybrid work policy for this role? A: Yes, many engineering and analyst positions based out of the Oakland, CA headquarters operate under a hybrid model. The exact split between remote work and in-office collaboration typically depends on the specific team and project requirements.

To maximize your chances of success during the PG&E hiring process, consider these targeted preparation strategies.

• Structure Your Presentation Wisely: Use clear visual diagrams to explain your project's architecture. Focus on the why behind your technology choices (e.g., why you chose Snowflake over a traditional relational database, or how you optimized AWS costs).

• Master the STAR Method: For both the automated HireView and the live panel behavioral questions, structure your answers using the Situation, Task, Action, and Result framework. Quantify your results wherever possible (e.g., "reduced query execution time by 40%").

• Brush Up on Core Utility Concepts: While you do not need to be an industry expert, having a basic understanding of how utility companies operate—and the types of data they handle (such as AMI smart meter data, geospatial asset data, and grid load metrics)—will show deep interest and alignment.

• Practice Live SQL and Python Execution: Practice writing clean code on a whiteboard or in a basic text editor without the help of auto-complete. Focus on writing readable code, explaining your thought process out loud, and testing your edge cases.

Securing a Data Engineer position at Pacific Gas and Electric is an exciting opportunity to work on highly impactful, large-scale data challenges that directly contribute to the safety, reliability, and clean energy transformation of California’s utility grid. Your ability to build robust data pipelines and architect modern cloud solutions will support critical operational decisions across the entire enterprise.

To succeed, focus your preparation on mastering live SQL and Python coding, refining your technical presentation to highlight your architectural decision-making, and aligning your behavioral stories with the company’s core values of safety, collaboration, and operational excellence. With a structured and dedicated preparation plan, you can confidently navigate each stage of the selection process.

The compensation for this position reflects the expert-level skills required to manage PG&E's critical data infrastructure. The competitive base salary is typically complemented by a comprehensive benefits package, retirement plans, and performance-based incentives, making it a highly rewarding career path for experienced data professionals.

To explore more real-world interview insights, practice questions, and preparation resources tailored to top companies, visit Dataford. Good luck with your preparation—your journey to powering the future of energy data starts now!