PG
PG&EData Platform Engineer
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Before you apply
Salary$49 – $78/hr
LocationOakland, CA, US
Work modehybrid
Typefull-time
SeniorityMid
Experience2+ yrs
DepartmentEngineering / Science
Company size10,000+ people
PostedOct 14, 2026 · 3w ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Bachelor's degree in computer science, job-related discipline, or equivalent experience
2 years of hands-on experience in infrastructure, systems administration, cloud operations, database support, or related Information Technology functions
1 year of experience supporting cloud technologies, cloud services, infrastructure automation, database technologies, or cloud-based operating environments
AWS Certified Data Engineer, Azure Data Engineer, database-related certification, or equivalent cloud platform certification
3 years of experience working with databases or data platforms
Hands-on experience supporting Microsoft SQL Server and/or PostgreSQL databases
Working knowledge of relational database concepts and SQL
Basic understanding of database administration concepts, including backup and recovery, security, performance, availability, and database maintenance
Experience working in an Agile/Scrum environment
Experience with database monitoring and troubleshooting tools and techniques
Experience with scripting using PowerShell, Python, Bash, SQL, or similar scripting technologies
Experience with SQL, Oracle, NoSQL, Aurora PostgreSQL, RDS, Azure SQL, and Redshift
Knowledge of cloud technologies and services, including EC2, Lambda, Terraform, S3, OCI, CI/CD, and containers
Experience with database and data platform migrations
Experience with data management
Understanding of Agile/Scrum principles and team-based delivery practices
Knowledge of continuous integration and continuous deployment practices and tools
Understanding of the AI development life cycle
Understanding of machine learning concepts, platforms, and operational workflows
Ability to deliver work in sprints and collaborate effectively with cross-functional teams
Skills
AWS
RDS
Aurora
Azure
Azure SQL
Cosmos DB
Synapse
SQL Managed Instance
S3
EBS
EFS
FSx
Blob Storage
Azure Files
Managed Disks
Data Lake Storage
Storage Spaces Direct
Azure Managed Disks
Microsoft SQL Server
PostgreSQL
Terraform
Azure DevOps
PowerShell
Python
Bash
SQL
Oracle
NoSQL
Aurora PostgreSQL
Redshift
EC2
Lambda
OCI
CI/CD
containers
Agile
Scrum
Benefits
Discretionary incentive compensation
Requisition ID # 174343
Job Category: Engineering / Science
About the role
Job Level: Individual Contributor
Business Unit: Technology & Security
Work Type: Hybrid
Job Location: Oakland
Department Overview
Technology & Security delivers secure, resilient, and scalable enterprise platforms that support critical business applications, infrastructure services, cloud operations, automation, and emerging technology enablement.
Position Summary
The Data Platform Engineer (DPE) builds, administers, and supports modern data and database infrastructure that enables advanced business capabilities across AWS (RDS, Aurora), Azure (Azure SQL, Cosmos DB, Synapse), and AzureLocal (SQL Managed Instance). The DPE manages cloud storage services, including AWS (S3, EBS, EFS, FSx), Azure (Blob Storage, Azure Files, Managed Disks, Data Lake Storage), and AzureLocal (Storage Spaces Direct, Azure Managed Disks).
The role focuses on designing reliable data pipelines and data structures that support analytics, AI, and machine learning workloads, while also providing project database administration and support for Microsoft SQL Server and PostgreSQL databases.
The DPE also integrates AI capabilities into database platforms to improve automation, optimization, and predictive maintenance. The role includes developing AI-driven workflows that support database maintenance, performance tuning, and data cleansing.
Infrastructure provisioning for database and storage resources is managed through Terraform, including multi-cloud resource provisioning, lifecycle policies, encryption, replication, and access control as code. Deployment automation is implemented through Azure DevOps pipelines, including database schema migrations, storage provisioning, backup validation, and environment promotion from DEV to PROD.
Legal
PG&E is providing the hourly rate range that the company in good faith believes it might pay for this position at the time of the job posting. This compensation range is specific to the locality of the job. The actual hourly rate paid to an individual will be based on multiple factors, including, but not limited to, specific skills, education, licenses or certifications, experience, market value, geographic location, and internal equity. This job is also eligible to participate in PG&E’s discretionary incentive compensation programs.
Benefits
The hourly rate for this position ranges from $49.04 to $77.88.
This position is hybrid, working from your remote office and 1-2 days per week at our Oakland Headquarters based on business need. The assigned work location will be within the PG&E Service Territory.
Job Responsibilities
Data Platform and Engineering
•
Build, test, and deploy data solutions and data pipelines for relational databases, data lakes, and data warehouses.
•
Build and implement data integrity, data cleansing, and data retention processes.
•
Create and manage data objects within cloud storage services.
•
Collect, review, and analyze data to support operational reliability and performance optimization.
•
Partner with application teams to identify, analyze, and resolve data inconsistencies.
•
Assist in implementing data quality controls, validation rules, reconciliation checks, schema drift handling, and automated exception reporting to improve trust in downstream analytics, AI, and reporting workloads.
•
Develop infrastructure-as-code modules and reusable deployment patterns for databases, storage accounts, networking dependencies, monitoring policies, backup configuration, replication, and environment promotion.
•
Support database and storage migrations from legacy or on-premises platforms to cloud-native architectures, including assessment, dependency mapping, cutover planning, validation, rollback planning, and post-migration optimization.
•
Provide project support for Microsoft SQL Server and PostgreSQL databases in production and non-production environments.
•
Assist with the installation, configuration, patching, and upgrading of SQL Server and PostgreSQL databases.
Qualifications
Minimum:
•
Bachelor’s degree in computer science, job-related discipline, or equivalent experience
•
2 years of hands-on experience in infrastructure, systems administration, cloud operations, database support, or related Information Technology functions
•
1 year of experience supporting cloud technologies, cloud services, infrastructure automation, database technologies, or cloud-based operating environments
•
AWS Certified Data Engineer, Azure Data Engineer, database-related certification, or equivalent cloud platform certification
Nice to have
Desired:
•
3 years of experience working with databases or data platforms.
•
Hands-on experience supporting Microsoft SQL Server and/or PostgreSQL databases.
•
Working knowledge of relational database concepts and SQL.
•
Basic understanding of database administration concepts, including backup and recovery, security, performance, availability, and database maintenance.
•
Experience working in an Agile/Scrum environment.
•
Experience with database monitoring and troubleshooting tools and techniques.
•
Experience with scripting using PowerShell, Python, Bash, SQL, or similar scripting technologies.
•
Experience with SQL, Oracle, NoSQL, Aurora PostgreSQL, RDS, Azure SQL, and Redshift.
•
Knowledge of cloud technologies and services, including EC2, Lambda, Terraform, S3, OCI, CI/CD, and containers.
•
Experience with database and data platform migrations.
•
Experience with data management.
•
Understanding of Agile/Scrum principles and team-based delivery practices.
•
Knowledge of continuous integration and continuous deployment practices and tools.
•
Understanding of the AI development life cycle.
•
Understanding of machine learning concepts, platforms, and operational workflows.
•
Ability to deliver work in sprints and collaborate effectively with cross-functional teams.