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Cloud Data Engineer Jobs in California (NOW HIRING)

SGS Consulting

AWS Cloud Data Engineer

San Francisco, CA · On-site

$65.75 - $87.75/hr

AWS Cloud Data Engineer Duration: 18 Months Location: San Francisco, CA Note: No C2C allowed in this role. We are seeking an experienced Lead Cloud Data Engineer to design and modernize enterprise ...

New

Hewlett Packard Enterprise

Cloud Data Engineer

San Jose, CA · On-site

$134K - $161K/yr

The Cloud Data Engineer will ensure the reliability, performance, and security of applications while collaborating with data scientists to design, build, and maintain data pipelines and services.

Hewlett Packard Enterprise

Cloud Data Engineer

San Jose, CA

$134K - $161K/yr

Cloud Data Engineer This role has been designed as ''Onsite' with an expectation that you will primarily work from an HPE office. Who We Are: Hewlett Packard Enterprise is the global edge-to-cloud ...

Kavaliro

Cloud Data Engineer

Napa, CA · On-site

$115K - $151K/yr

The Cloud Data Engineer's responsibilities include designing, implementing, and managing data solutions on Microsoft Azure and other cloud platforms. Oversee the creation and maintenance of data ...

Redwood Credit Union

Cloud Data Engineer

Napa, CA

$115K - $151K/yr

Redwood Credit Union is looking for a Cloud Data Engineer, responsibilities include designing, implementing, and managing data solutions on Microsoft Azure and other cloud platforms. Oversee the ...

Redwood Credit Union

Cloud Data Engineer

Napa, CA · On-site

$115K - $151K/yr

Redwood Credit Union is looking for a Cloud Data Engineer, responsibilities include designing, implementing, and managing data solutions on Microsoft Azure and other cloud platforms. Oversee the ...

Evolver Commercial

Senior Cloud Data Engineer

San Francisco, CA · On-site

$124K - $169K/yr

Evolver is seeking an experienced, highly skilled cloud data engineer to provide services to our Investment Operations & Fund Treasury Data Engineering team. The ideal resource will have experience ...

New

Redwood Credit Union

Cloud Data Engineer

Santa Rosa, CA · On-site

$115K - $151K/yr

Redwood Credit Union is looking for a Cloud Data Engineer, responsibilities include designing, implementing, and managing data solutions on Microsoft Azure and other cloud platforms. Oversee the ...

Redwood Credit Union

Cloud Data Engineer

Santa Rosa, CA

$115K - $151K/yr

Redwood Credit Union is looking for a Cloud Data Engineer, responsibilities include designing, implementing, and managing data solutions on Microsoft Azure and other cloud platforms. Oversee the ...

Redwood Credit Union

Cloud Data Engineer

Santa Rosa, CA

$115K - $151K/yr

Redwood Credit Union is looking for a Cloud Data Engineer, responsibilities include designing, implementing, and managing data solutions on Microsoft Azure and other cloud platforms. Oversee the ...

Cloud BC Labs

AWS Data Engineer

Alameda, CA · On-site

$129K - $155K/yr

Proven experience in leading data engineering projects and mentoring junior Cloud BC Labs Inc is a digital transformation organization aimed at creating seamless solutions for clients to effectively ...

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Cloud Data Engineer information

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How much do cloud data engineer jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for cloud data engineer in California is $62.06, according to ZipRecruiter salary data. Most workers in this role earn between $52.88 and $70.67 per hour, depending on experience, location, and employer.

What are some common challenges a cloud data engineer faces when migrating data to the cloud?

Cloud Data Engineers often encounter challenges such as ensuring data security and compliance during migration, optimizing data pipelines for cloud performance, and managing data integrity across distributed systems. They must work closely with cross-functional teams to minimize downtime and avoid data loss, and frequently address issues related to data format compatibility and legacy system integration. Staying up-to-date with evolving cloud technologies and best practices is also essential for successful data migration projects.

What is the difference between Cloud Data Engineer vs Data Analyst?

AspectCloud Data EngineerData Analyst
Required CredentialsCloud certifications (e.g., AWS, Azure), SQL, programming skillsData analysis certifications, SQL, Excel, visualization tools
Work EnvironmentCloud platforms, big data tools, data pipelinesData visualization, reporting, business insights
Employer & Industry UsageTech companies, finance, healthcare, cloud service providersMarketing, finance, retail, business intelligence

While Cloud Data Engineers focus on building and maintaining cloud-based data infrastructure, Data Analysts interpret data to provide business insights. Both roles require SQL skills, but Cloud Data Engineers emphasize cloud platforms and data pipeline development, whereas Data Analysts focus on data visualization and reporting.

What are the key skills and qualifications needed to thrive as a cloud data engineer?

To excel as a Cloud Data Engineer, you need strong expertise in data modeling, ETL processes, programming languages like Python or SQL, and a solid understanding of cloud platforms such as AWS, Azure, or Google Cloud, often supported by a relevant degree and cloud certifications. Familiarity with tools like Apache Spark, Hadoop, cloud storage systems, and data pipeline orchestration frameworks is typically required. Strong problem-solving skills, attention to detail, and effective communication help you deliver scalable solutions and collaborate with cross-functional teams. These competencies are essential for building robust, secure, and efficient data infrastructure that supports business intelligence and analytics.

What does a cloud data engineer do?

A cloud data engineer designs, builds, and maintains data pipelines and storage solutions in cloud environments such as AWS, Azure, or Google Cloud. They work with big data tools, manage data security, and optimize data workflows to support analytics and business intelligence. Proficiency in programming, database management, and cloud services is essential for this role.

What is a cloud data engineer?

A Cloud Data Engineer is an IT professional who designs, builds, and manages scalable data infrastructure and pipelines in cloud environments. They work with cloud platforms like AWS, Google Cloud, or Azure to create systems that collect, process, store, and analyze large volumes of data. Their responsibilities include setting up data lakes and warehouses, ensuring data quality and security, and enabling data-driven applications. Cloud Data Engineers collaborate with data scientists, analysts, and other stakeholders to support business intelligence and analytics initiatives.

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

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

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

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

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

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

What cities in California are hiring for Cloud Data Engineer jobs?

Cities in California with the most Cloud Data Engineer job openings:

Cloud Data Engineer jobs near you
Infographic showing various Cloud Data Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 2% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $129,089 per year, or $62.1 per hour.

AWS Cloud Data Engineer

SGS Consulting

San Francisco, CA • On-site

$65.75 - $87.75/hr

Other

Posted 2 days ago

New

Job description

Job Title:         

AWS Cloud Data Engineer

Duration:        

18 Months

Location:    

San Francisco, CA

Note: No C2C allowed in this role. 

Job Description:

We are seeking an experienced Lead Cloud Data Engineer to design and modernize enterprise-scale data platforms using AWS, Data Mesh architecture, and AI-driven solutions. This role will lead the development of scalable data pipelines, cloud infrastructure, and AI-enabled engineering practices while mentoring technical teams and supporting enterprise data modernization initiatives.

Job Responsibilities:

  • Design, build, and maintain scalable ETL/ELT data pipelines using AWS services (Glue, EMR, Lambda, Kinesis, Step Functions).
  • Develop and implement Data Mesh architecture with domain-driven data products and federated governance.
  • Build modern cloud data platforms using Databricks, Delta Lake, Starburst/Trino, Collibra, and Immuta.
  • Implement data governance, metadata management, data lineage, and automated data quality frameworks.
  • Develop reusable frameworks and self-service tools for data publishing and consumption.
  • Integrate DevSecOps practices including CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), and security automation.
  • Design AI-powered solutions, RAG pipelines, and agentic AI applications using Amazon Bedrock or similar LLM platforms.
  • Provide technical leadership, mentor engineering teams, and support L3 production issues.
  • Collaborate with business stakeholders to translate requirements into scalable cloud data solutions.
  • Lead architecture reviews, technical documentation, and performance optimization initiatives.

Basic Qualifications:

  • 7+ years of experience in Data Engineering, Cloud Data Platforms, or Data Architecture.
  • Strong hands-on experience with AWS services including S3, Glue, EMR, Redshift, Lake Formation, Lambda, and Kinesis.
  • Experience implementing Data Mesh architecture and modern data platforms using Databricks, Delta Lake, Starburst/Trino, Collibra, or Immuta.
  • Proficiency in DevSecOps, CI/CD, Terraform/CloudFormation, Docker, and AI technologies such as Amazon Bedrock, RAG, or Generative AI.

Additional Information:

  • Lead-level position requiring the ability to work independently with minimal supervision.
  • Experience working in hybrid cloud and on-premises enterprise environments is highly preferred.
  • Strong communication, leadership, and mentoring skills are essential.
  • Candidates with experience supporting government or regulated AWS environments (GovCloud) are highly preferred.

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