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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

Cloud Data Engineering * Design, develop, and maintain scalable ETL/ELT data pipelines using AWS Glue, EMR, Lambda, Kinesis, and Step Functions. * Build ingestion frameworks for structured, semi ...

Purple Drive

Alibaba Cloud Data Engineer

Sunnyvale, CA · On-site

$63.25 - $84.50/hr

Experience with real-time data streaming (Kafka, Flink, etc.) and data analytics (Spark, Airflow). * Knowledge of cloud networking and security on Alicloud. * Exposure to DevOps practices (Terraform ...

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.

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 ...

Hewlett Packard Enterprise

Cloud Data Engineer

San Jose, CA · On-site

$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 ...

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 ...

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 · 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 ...

AaraTechnologies Inc

DATA ENGINEER

California City, CA · On-site

$140K - $168K/yr

Data Engineer Healthcare (2-3 Years Experience) Company: AaraTech Inc About the Role AaraTech Inc ... Exposure to AWS or cloud data platforms * Strong analytical and problem-solving skills Skills SQL ...

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 ...

Hyundai MOBIS

Data Engineer III, Cloud

Fountain Valley, CA · On-site

$125K - $150K/yr

Data Engineer III, Cloud We are searching for an experienced Data Engineer III, Cloud at our Headquarters facility. Hyundai MOBIS Parts America We think creatively and keep challenging ourselves to ...

Hyundai MOBIS

Data Engineer III, Cloud

Fountain Valley, CA

$125K - $151K/yr

Job Purpose The Cloud Data Engineer is responsible for designing, implementing, maintaining, and securing Azure-based data platforms. This role builds and manages data pipelines, data storage ...

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Cloud Data Engineer information

See California salary details

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How much do cloud data engineer jobs pay per hour?

As of Sep 4, 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 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 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 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 does a cloud data engineer do?

A cloud data engineer designs, builds, and maintains data pipelines and infrastructure in cloud environments such as AWS, Azure, or Google Cloud. They work with big data tools, manage data storage, and ensure data quality and security to support analytics and business decision-making.

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 75% Full Time, and 25% Contract. Highlights an 88% In-person, and 12% 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 23 days ago

Job description

Description:

We are seeking an experienced AWS Cloud Data Engineer to lead the design, development, and modernization of enterprise-scale cloud data platforms. This role will focus on building modern Data Mesh architectures, developing scalable AWS-based data pipelines, implementing DevSecOps best practices, and integrating AI-powered solutions to accelerate software development and data engineering initiatives.

The ideal candidate will possess strong expertise in AWS cloud services, enterprise data architecture, distributed data platforms, governance frameworks, and modern AI technologies.

Key Responsibilities:

Cloud Data Engineering

  • Design, develop, and maintain scalable ETL/ELT data pipelines using AWS Glue, EMR, Lambda, Kinesis, and Step Functions.
  • Build ingestion frameworks for structured, semi-structured, streaming, and API-based data sources.
  • Develop optimized data models and consumption layers for enterprise analytics.
  • Implement automated data quality validation, monitoring, alerting, and anomaly detection.
  • Maintain metadata management, data lineage, governance, and access control policies

Data Mesh Architecture

  • Design and implement enterprise Data Mesh architecture on AWS.
  • Define domain ownership, data products, federated governance, and self-service data infrastructure.
  • Build reusable frameworks and accelerators for publishing, discovering, and consuming data products.
  • Optimize platform performance, scalability, and cloud cost efficiency.

Modern Data Platforms

Work extensively with technologies including:

  • Databricks
  • Unity Catalog
  • Delta Lake
  • Starburst / Trino
  • Collibra
  • Immuta

DevSecOps & Cloud Infrastructure

  • Implement CI/CD pipelines using GitHub Actions, GitLab CI, or Jenkins.
  • Develop Infrastructure as Code using Terraform and CloudFormation.
  • Deploy and manage containerized applications using Docker and Amazon ECS.
  • Implement automated security scanning, compliance validation, disaster recovery, and AWS GovCloud security controls.

AI-Augmented Engineering

  • Design and develop Agentic AI solutions and Retrieval-Augmented Generation (RAG) pipelines.
  • Utilize Amazon Bedrock and enterprise LLMs for intelligent automation.
  • Leverage AI-assisted development tools such as GitHub Copilot and Claude Code.
  • Improve software delivery through AI-powered code generation, testing, documentation, and automation.

Technical Leadership

  • Lead architecture reviews and technical design discussions.
  • Mentor engineering teams on modern cloud data engineering practices.
  • Provide Level 3 production support.
  • Collaborate with architects, product owners, and business stakeholders to deliver scalable enterprise solutions.
  • Produce technical documentation and architectural standards.

Required Qualifications:

Cloud Data Engineering & AWS (5+ Years)

  • 5+ years of hands-on experience designing and implementing distributed data architectures on AWS.
  • Strong expertise with AWS services including:
    • Amazon S3
    • AWS Glue
    • AWS Lake Formation
    • Amazon EMR
    • Amazon Redshift
  • Experience building scalable ETL/ELT pipelines and enterprise data platforms.

Data Mesh Architecture

  • Hands-on experience implementing Data Mesh architecture and modern distributed data platforms.
  • Strong understanding of:
    • Domain-oriented data ownership
    • Data as a Product
    • Federated Computational Governance
    • Self-service data infrastructure
  • Experience designing scalable, domain-driven data solutions.

Modern Data Platform Technologies

Hands-on experience with one or more of the following enterprise data platforms:

  • Databricks (Unity Catalog, Delta Lake)
  • Starburst / Trino (Federated Query)
  • Collibra (Data Governance & Metadata Management)
  • Immuta (Dynamic Data Access Control)
  • Ability to architect and integrate multi-platform data solutions across enterprise environments.

DevSecOps & Infrastructure as Code (IaC)

  • Strong experience implementing DevSecOps best practices throughout the software development lifecycle.
  • Hands-on experience with:
    • CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins)
    • Containerization technologies (Docker, Amazon ECS)
    • Infrastructure as Code (Terraform, AWS CloudFormation)
  • Experience implementing security, compliance, and governance controls within AWS cloud environments, including AWS GovCloud.

AI-Augmented Development & Engineering

  • Experience leveraging Generative AI tools to improve software development productivity through:
    • Code generation
    • Automated testing
    • Documentation
    • SDLC acceleration
  • Hands-on experience designing or implementing:
    • Agentic AI solutions
    • Retrieval-Augmented Generation (RAG) pipelines
    • Amazon Bedrock or similar Large Language Model (LLM) platforms

Leadership & Communication

  • Proven ability to translate complex business requirements into scalable technical solutions.
  • Experience leading technical design discussions, architecture reviews, and engineering initiatives.
  • Demonstrated ability to mentor and guide engineering teams.
  • Excellent verbal and written communication skills with the ability to present complex technical concepts to both technical and non-technical stakeholders.
  • Experience working across hybrid cloud and on-premises enterprise environments.

Apply