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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer, Expert - **Company:** PG&E Corporation - **Location:** Oakland, CA, United States - **Experience:** Expert - **Salary:** $291,200.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Geographic Information Systems, Airflow, Amazon Web Services, Amazon S3, ArcGIS (Software), Unit Testing, Continuous Delivery, Continuous Integration, Information Engineering, Data Integration, Extract Transform Load (ETL), Distributed Computing Environment, Amazon DynamoDB, Github, Python (Programming Language), Machine Learning, Meta-Data Management, Oracle Business Intelligence Enterprise Edition, Power BI, Cloud Services, SAP (Applications), Amazon Simple Notification Service (SNS), SQL Databases, Tableau (Software), Unstructured Data, Test-Driven Development (TDD), Informatica Powercenter, Snowflake, Palantir Foundry, Apache Spark, State Machines, Git, Cloudformation, Infrastructure Automation Frameworks, Information Technology, Data Lineage, Collibra, AWS Glue, Cloudwatch, Amazon Simple Queue Service (SQS), Terraform, Software Version Control, Data Pipelines, Amazon Redshift, Databricks, Programming Languages - **Published:** October 29, 2026 - **Apply:** https://jobs.pge.com/job/oakland/data-engineer-expert/29673/102568420448 ## About the Role * BA/BS in computer science, Management Information Systems or related field of study, or equivalent experience * 7 years of experience with data engineering/ETL ecosystems such as Palantir Foundry, Spark, Informatica, SAP BODS, OBIEE. * Experience with multiple data engineering/ETL ecosystems. * Experience with machine learning algorithm deployment., + Master's degree in Computer Science, Management Information Systems, or related field of study, or equivalent experience + Hands-on experience in data engineering, including: o # Designing and building scalable ETL/ELT pipelines for structures, semi-structures, and unstructured data. # Working with cloud data platforms such as Snowflake Databricks, or AWS Redshift # Using data integration tools like Informatica or AWS Glue # Developing in distributed data processing frameworks such as Apache Spark + Proficiency in SQL and at least one programming language such as: Python, Scala, or Java + Ability to collaborate in cross-functional teams and communicate technical concepts to non-technical stakeholders + Strong understanding of software engineering best practices, including: o # Unit testing and test-driven development (TDD) # Continuous integration/Continuous Deployment (CI/CD) # Source control using tools like Git and platforms like GitHub + Experience with cloud services (preferably AWS), including: o # S3, Lambda, Step Functions, Fargate, DynamoDB, SNS/SQS, and CloudWatch. + Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation). + Experience deploying and operationalizing machine learning models in production environments] + Familiarity with business intelligence tools such as PowerBI, Tableau, or Foundry for data visualization and reporting. + Experience working with geospatial data and tools such as ArcGIS + Experience with data cataloging, metadata management, and data lineage tools such as informatica and Collibra. ## Description PG&E is seeking an Expert Data Engineer to lead the development of a modern, cloud-native data platform that supports vegetation management operations, regulatory compliance, and advanced analytics. This role is central to transforming fragmented legacy systems into a unified, audit-ready Snowflake Data Lakehouse, enabling scalable, secure, and transparent data access across the organization., The engineer will design and implement robust ELT pipelines using Snowflake, Airflow, Informatica, and a suite of AWS services including Step Functions, Fargate, Lambda, DynamoDB, and S3. The role spans structured, semi-structured, and unstructured data domains, integrating sources such as Salesforce (OneVM), SAP, SharePoint, ArcGIS, and remote sensing imagery (LiDAR, orthoimagery, surface reflectance, etc.)., * Design, build, and maintain scalable data pipelines using tools such as Airflow, Informatica, AWS services, and Snowflake to support ingestion, transformation, and curation of structured, semi-structured, and unstructured data. * Collaborate with cross-functional teams - including data scientists, analysts, and business stakeholders - to understand data requirements and deliver high-quality, analytics-ready datasets. * Implement and optimize data lakehouse architectures, ensuring efficient data flow across Bronze, Silver, and Gold layers in Snowflake. * Support the deployment of machine learning models by enabling feature pipelines, model input/output data flows, and integration with platforms like SageMaker or Foundry. * Apply software engineering best practices such as version control, CI/CD, unit testing, and infrastructure-as-code to ensure reliable and maintainable data workflows. * Monitor and troubleshoot data pipelines, ensuring data quality, lineage, and governance standards are met across all environments. * Mentor junior engineers and contribute to architectural decisions, code reviews, and knowledge sharing within the team. * Communicate technical concepts and project updates clearly to both technical and non-technical audiences.