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Contract Data Platform Engineer Jobs in California

Data Platform Engineer

Oakland, CA ยท Hybrid

$49.04 - $77.88/hr

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

Data Platform Engineer

San Francisco, CA ยท On-site

$200K - $250K/yr

As a Data Platform Engineer at Astronomer, you'll be a key partner to our clients, guiding them in deploying powerful data workflows to accelerate their business outcomes. You'll have the chance to ...

AI Data Platform Engineer

Cupertino, CA ยท On-site

$141K - $169K/yr

As an AI Data Platform Engineer with the MSI team, you will design, build, and operate scalable AI data platforms that enable GenAI, Agentic AI, and Embodied AI solutions across the enterprise. You ...

AI Data Platform Engineer

Cupertino, CA ยท On-site

$141K - $169K/yr

As an AI Data Platform Engineer with the MSI team, you will design, build, and operate scalable AI data platforms that enable GenAI, Agentic AI, and Embodied AI solutions across the enterprise. You ...

As an AI Data Platform Engineer with the MSI team, you will design, build, and operate scalable AI data platforms that enable GenAI, Agentic AI, and Embodied AI solutions across the enterprise. You ...

Data Platform Engineer

San Francisco, CA ยท On-site

$134K - $162K/yr

They are seeking Founding- and Staff-level Engineers to design and implement the foundational pillars of their data platform, enabling the ingestion and normalization of enterprise data sources for ...

AI Data Platform Engineer

Cupertino, CA ยท On-site

$141K - $169K/yr

As an AI Data Platform Engineer with the MSI team, you will design, build, and operate scalable AI data platforms that enable GenAI, Agentic AI, and Embodied AI solutions across the enterprise. You ...

Data Platform Engineer, Data Pipelines

Irvine, CA ยท On-site

$122K - $147K/yr

About the Job As a Data Platform Engineer, Data Pipelines , you will design and build the systems ... Own integration reliability end to end: schema contracts, versioning, retries, backfills, and ...

Data Platform Engineer, Data Pipelines

Irvine, CA ยท On-site

$122K - $147K/yr

About the Job As a Data Platform Engineer, Data Pipelines , you will design and build the systems ... Own integration reliability end to end: schema contracts, versioning, retries, backfills, and ...

Data Platform Engineer, Data Pipelines

Irvine, CA ยท On-site

$122K - $147K/yr

About the Job As a Data Platform Engineer, Data Pipelines, you will design and build the systems ... Own integration reliability end to end: schema contracts, versioning, retries, backfills, and ...

Data Platform Engineer, Data Pipelines

Irvine, CA ยท On-site

$122K - $147K/yr

About the Job As a Data Platform Engineer, Data Pipelines , you will design and build the systems ... Own integration reliability end to end: schema contracts, versioning, retries, backfills, and ...

Data Platform Engineer, Infrastructure

Irvine, CA ยท On-site

$115K - $151K/yr

About the Job As a Data Platform Engineer, Infrastructure , you will build and operate the cloud foundation the entire data platform runs on - the systems every robot log, dashboard, and model ...

Data Platform Engineer, Infrastructure

Irvine, CA ยท On-site

$115K - $151K/yr

About the Job As a Data Platform Engineer, Infrastructure , you will build and operate the cloud foundation the entire data platform runs on -- the systems every robot log, dashboard, and model ...

Showing results 21-40

Contract Data Platform Engineer information

What is the difference between Contract Data Platform Engineer vs Contract Data Engineer?

AspectContract Data Platform EngineerContract Data Engineer
Primary FocusBuilding and maintaining data infrastructure and platformsDeveloping and optimizing data pipelines and workflows
Skills & CertificationsCloud platforms, data architecture, scripting, certifications like AWS or GCPSQL, ETL tools, programming languages, data modeling
Work EnvironmentCollaborates with data platform teams, cloud environments, infrastructure focusWorks on data pipelines, analytics, and data processing tasks
Industry UsageUsed in organizations with complex data infrastructure needsCommon in data-driven companies focusing on data analysis and reporting

The Contract Data Platform Engineer primarily focuses on designing and maintaining data infrastructure and platforms, often working with cloud services and architecture. In contrast, the Contract Data Engineer concentrates on developing data pipelines and processing workflows. Both roles require strong data skills, but their focus areas differ, making them suitable for different project needs within data teams.

What are the most commonly searched types of Data Platform Engineer jobs in California?

The most popular types of Data Platform Engineer jobs in California are:

What are popular job titles related to Contract Data Platform Engineer jobs in California?

For Contract Data Platform Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Contract Data Platform Engineer jobs in California look for?

The top searched job categories for Contract Data Platform Engineer jobs in California are:

What cities in California are hiring for Contract Data Platform Engineer jobs?

Cities in California with the most Contract Data Platform Engineer job openings:

Data Platform Engineer

Oakland, CA โ€ข Hybrid

$49.04 - $77.88/hr

Full-time

This job post hasย expired 3 days ago.ย Applications are no longer accepted.


Job description

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 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.


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&Eโ€™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.โ€ฏ 

Job 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.

Qualifications

Minimum:

  • 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

Desired:

  • 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