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Salary
$98k – $154k per year
Location
Hybrid (Oakland, United States)
Seniority
Middle · 3+ years exp

Confirmed on the employer's own hiring board on Nov 13, 2026. First seen by Alion on Oct 29, 2026.

Overview
Company
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Requisition ID # 174343

Job Category: Engineering / Science

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.

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.

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

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.
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