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# Data Platform Engineer

- **Company:** PG&E Corporation
- **Location:** Oakland, CA, United States
- **Salary:** $102,003.0 - $161,990.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Data Analysis, Microsoft Azure, Bash Shell, Cloud Computing, Cloud Engineering, Cloud Storage, Databases, Continuous Delivery, Continuous Integration, Data Cleansing, Data Infrastructure, Data Integrity, Data Retention, Data Structures, Data Systems, Data Warehousing, Relational Databases, Database Schema, Python (Programming Language), PostgreSQL, Machine Learning, Microsoft SQL Server, SQL Azure, NoSQL, Oracle (Applications), Performance Tuning, Windows PowerShell, Scrum Methodology, Cloud Services, Azure DevOps Pipelines, SQL Databases, Diagnostic Tools, Scripting, Cloud Platform System, Azure Data Factory, Multi-Cloud, Amazon Relational Database Service, Data Lakes, Infrastructure Automation Frameworks, Information Technology, Deployment Automation, Cosmos DB, Data Management, Data Objects, Functional Programming, Database Monitoring, Terraform, Oracle Cloud Infrastructure, Azure Synapse Analytics, Data Inconsistencies, Data Pipelines, Amazon Redshift
- **Published:** November 3, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=01dcb286c7eb296a

## About the Role

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.

## Description

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., 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.