Data Platform Engineer

PG&E•Oakland, CA

6d•Hybrid

About The Position

The Data Platform Engineer (DPE) builds and supports modern data infrastructure that enables advanced business capabilities across AWS (RDS, Aurora, DynamoDB, Redshift), 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. 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.

Requirements

Bachelor's degree in computer science, job-related discipline, or equivalent experience
2 years experience in infrastructure, systems administration, cloud operations, or related Information Technology functions
1 year of experience supporting cloud technologies, cloud services, infrastructure automation, or cloud-based operating environments
AWS Certified Data Engineer or Azure Data Engineer or equivalent cloud platform certification

Nice To Haves

3 years of experience with databases.
Experience working in an Agile/Scrum environment
Knowledge of cloud technologies and services, including EC2, Lambda, Terraform, S3, OCI, and CI/CD, and containers
Experience with SQL, Oracle, NoSQL, Aurora Postgres, RDS, and Redshift
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
Experience with scripting

Responsibilities

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 data objects within cloud storage services.
Troubleshoot, maintain, and install software components related to databases.
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 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.
Plan and execute 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.