Preparing for an interview at PG&E requires a balanced approach that covers core technical skills, architectural design principles, and behavioral competencies. You should approach your preparation with the mindset of a systems builder who values safety, reliability, and clear communication.

Technical Excellence – You must demonstrate deep proficiency in SQL and Python, as these are the primary tools used for data manipulation. Be prepared for live coding sessions where performance and edge-case handling are evaluated. Additionally, ensure you are comfortable discussing modern cloud data warehouses, specifically Snowflake, and how to optimize them.

Architectural & Pipeline Design – Interviewers want to see how you approach high-level system design. You should practice structuring data pipelines from ingestion to consumption, paying close attention to scalability, data quality checks, and error handling. Be ready to justify your choice of tools and frameworks based on specific operational constraints.

Communication & Presentation Skills – A unique aspect of the PG&E interview process is the technical presentation. You must be able to articulate complex technical concepts clearly, structure a narrative around a past project, and defend your technical decisions during a live Q&A session with a panel of engineers.

Culture & Safety Mindset – As a utility company, PG&E places an absolute premium on safety, compliance, and reliability. Your behavioral answers should reflect a commitment to quality, thorough testing, and collaborative problem-solving. Show that you understand the real-world impact of your data pipelines.

The interview process for a Data Engineer at PG&E is structured to thoroughly evaluate both your technical capabilities and your communication skills. While the process is highly professional and respectful, candidates should be prepared for potential administrative delays, as the gap between interview stages can sometimes be lengthy.

The journey typically begins with an online application, followed by a recruiter phone screen to gather basic information regarding your education, work experience, and salary expectations. From there, the process splits into asynchronous and live evaluation stages, designed to test your coding abilities, architectural knowledge, and presentation skills.

The final stages involve deep technical dives and panel presentations where you will interact directly with the hiring manager and senior members of the engineering team. This comprehensive approach ensures that you possess both the hands-on coding skills and the strategic communication abilities required to succeed in the role.

The timeline above outlines the standard progression from your initial application to the final offer stage. Candidates should use this visualization to pace their preparation, ensuring they allocate sufficient time to practice live coding before the technical screen and refine their presentation slides ahead of the final panel. Because timelines can vary depending on the hiring team's schedule, maintaining consistent preparation throughout the process is key.

To succeed in the PG&E interview loop, you must excel across several distinct evaluation areas. Understanding what interviewers look for in each area will help you tailor your preparation effectively.

Cloud Data Warehousing & ETL

This area evaluates your ability to design and maintain robust data storage and transformation systems. At PG&E, you will handle massive volumes of operational and customer data, making storage efficiency and query performance paramount.

Be ready to go over:

• Snowflake Architecture – Virtual warehouses, micro-partitioning, clustering keys, and zero-copy cloning.
• AWS Integration – Utilizing S3 for data lakes, IAM roles for security, and services like AWS Glue or Lambda for serverless ETL.
• Data Modeling – Designing schemas (Star, Snowflake, Data Vault) that balance write performance with read simplicity for analysts.
• Advanced concepts (less common) – Implementing stream-processing pipelines using tools like Kafka or Spark Streaming for real-time grid monitoring.

Example scenarios:

• "Design a pipeline that ingests continuous stream data from smart meters, stores it in an AWS S3 data lake, and loads it into Snowflake for daily reporting."
• "Explain how you would troubleshoot a sudden spike in Snowflake credit consumption caused by a newly deployed ETL job."

Live Coding (SQL & Python)

You will face a live coding session designed to test your hands-on programming skills. The focus is on writing clean, readable, and performant code to solve practical data manipulation problems.

Be ready to go over:

• SQL Window Functions – Using RANK(), ROW_NUMBER(), LEAD(), and LAG() to analyze sequential data like meter readings.
• Python Data Libraries – Manipulating datasets efficiently using Pandas, NumPy, or built-in Python data structures.
• Error Handling & Logging – Writing robust code that handles null values, malformed inputs, and connection timeouts gracefully.

Example scenarios:

• "Write a SQL query to find the continuous duration of power outages for each substation, grouping by region."
• "Write a Python script that reads a directory of CSV files, cleanses inconsistent date formats, and outputs a consolidated JSON file."

Technical Project Presentation

A defining feature of the PG&E hiring process for Data Engineers is the 10-minute technical presentation on a project of your choice, followed by a Q&A session with a panel of engineers.

Be ready to go over:

• Problem Statement – What business or technical challenge were you trying to solve?
• Architecture Diagram – A clear visual representation of the data flow and technologies used.
• Your Individual Contribution – Clearly isolate what you built versus what the broader team did.
• Trade-off Analysis – Why did you choose specific tools (e.g., Snowflake over Redshift, or Python over Scala)?
• Key Metrics – Quantifiable outcomes, such as pipeline run-time reduction, cost savings, or data quality improvements.

Behavioral & Operational Scenarios

This section evaluates your soft skills, alignment with company values, and how you navigate the complexities of working within a large, regulated utility environment.

Be ready to go over:

• Collaboration – Working with cross-functional teams, including data scientists, business analysts, and field operations.
• Prioritization – Managing competing demands from multiple stakeholders under tight deadlines.
• Dealing with Ambiguity – Designing pipelines when source data specifications are incomplete or constantly changing.

Example scenarios:

• "Tell me about a time when a critical pipeline failed in production. How did you communicate the issue to stakeholders, and what steps did you take to prevent it from happening again?"
• "Describe a situation where you had to influence a team to adopt a new data engineering tool or practice."

As a Data Engineer at PG&E, your day-to-day responsibilities will revolve around building and maintaining the data pipelines that power the utility's modern grid initiatives. You will work closely with data scientists, business analysts, and IT infrastructure teams to ensure that clean, reliable data is accessible across the organization.

You will be responsible for designing and implementing robust ETL/ELT pipelines to ingest data from a wide variety of sources, including physical grid assets, weather sensors, and customer billing systems. You will optimize data storage and query performance within Snowflake, ensuring that business intelligence tools can run reports efficiently without incurring unnecessary cloud costs.

In addition to building new pipelines, you will play a key role in data governance and quality assurance. You will establish monitoring and alerting systems to detect data anomalies or pipeline failures early, ensuring that downstream operational decisions are made using accurate data. You will also contribute to documentation and code reviews, helping to maintain high engineering standards across the team.

To be competitive for the Data Engineer position at PG&E, you must possess a strong blend of core technical skills, cloud architecture experience, and professional soft skills.

• Must-have skills

  • Strong proficiency in writing complex, optimized SQL queries for data analysis and transformation.
  • Hands-on experience programming in Python for data pipeline development and automation.
  • Proven experience building data pipelines and managing data warehouses in cloud environments, specifically Snowflake and AWS.
  • Solid understanding of ETL/ELT design patterns, data modeling concepts, and data warehousing best practices.

• Nice-to-have skills

  • Experience working with streaming data technologies such as Apache Kafka or AWS Kinesis.
  • Familiarity with workflow orchestration tools like Apache Airflow.
  • Prior experience working in the utility, energy, or critical infrastructure sectors.
  • Knowledge of geospatial data processing (GIS) and handling spatial datasets.

Q: How difficult is the Data Engineer interview process at PG&E? A: Candidates generally describe the interview process as easy to average in difficulty. The technical questions focus on core data engineering concepts, practical SQL/Python coding, and cloud architecture rather than abstract, highly theoretical algorithmic puzzles.

Q: How much preparation time is typically recommended? A: We recommend dedicating 2 to 3 weeks of focused preparation. This allows you ample time to refresh your SQL and Python coding skills, structure your 10-minute technical presentation, and practice behavioral questions using the STAR method.

Q: What is the typical timeline from the initial application to an offer? A: The overall timeline can be quite long, sometimes taking several weeks to a couple of months. While the individual interview stages are structured and professional, candidates frequently report long waiting periods between the different steps of the process.

Q: What is the hybrid or remote work policy for Data Engineers at PG&E? A: PG&E generally operates under a hybrid work model, particularly for roles based out of their headquarters in Oakland, CA. You should expect a mix of remote work and scheduled in-office days for team collaboration, though exact requirements can vary by team.

To maximize your chances of success during the PG&E hiring process, keep the following practical tips in mind:

• Perfect Your Presentation Timing: The 10-minute presentation limit is strictly enforced during the final panel. Practice your presentation multiple times to ensure you cover all key points—problem, architecture, your contribution, and impact—without rushing or running over time.
• Emphasize Safety and Reliability: In your behavioral responses, highlight your commitment to thorough testing, data validation, and building resilient systems. PG&E is a safety-first organization, and this mindset should extend to how you manage data infrastructure.

• Use the STAR Method: When answering behavioral questions, structure your responses using the Situation, Task, Action, and Result framework. Be highly specific about the actions you took and quantify the final results whenever possible.
• Be Patient with the Process: Because there can be long gaps between interview stages, do not get discouraged by a lack of immediate feedback. Use the downtime to refine your technical presentation and continue practicing your coding skills.

Securing a Data Engineer role at PG&E offers an exceptional opportunity to apply modern data technologies to real-world, high-stakes challenges. By building and optimizing pipelines that support grid operations and clean energy integration, your work will have a tangible, positive impact on millions of lives.

To succeed, focus your preparation on mastering core SQL and Python concepts, understanding cloud architecture patterns in Snowflake and AWS, and crafting a polished, high-impact technical presentation. Combine this technical readiness with a collaborative, safety-conscious mindset to demonstrate that you are a complete, well-rounded candidate.

As you prepare to take the next steps in your career journey, remember that thorough preparation is your greatest asset. For additional real-world interview insights, community feedback, and preparation resources, you can explore further materials on Dataford to help you feel fully confident on interview day.

The salary data shown above represents the typical compensation range for data engineering professionals. When evaluating an offer from PG&E, remember to consider the complete compensation package, which often includes a base salary, performance-based bonuses, comprehensive health benefits, and retirement matching programs. Your specific offer will depend on your experience level, technical expertise, and the location of the role.