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Dataops Engineer Jobs in California (NOW HIRING)

Marencor

AWS Data Engineer

San Francisco, CA · On-site

$134K - $162K/yr

Role: AWS Data Engineer (Python, Dataiku) Location: SFO, CA - Hybrid Job Brief As an AWS Data ... Familiarity with DataOps concepts and tooling for source control and setting up CI/CD pipelines on ...

NextData

Senior Sales Engineer

San Francisco, CA · On-site

Experience with AI/ML platforms , MLOps, DataOps or developer platforms * Cloud and data engineering certifications * Public speaking or thought leadership experience in data infrastructure or ...

Socket.dev

Data Platform Engineer

San Francisco, CA · On-site

$200K - $250K/yr

... DataOps platform powered by Apache Airflow ® . Astro accelerates building reliable data products ... As a Data Platform Engineer at Astronomer, you'll be a key partner to our clients, guiding them in ...

Vast

Senior Data Engineer

Long Beach, CA · On-site

$143K - $203K/yr

Knowledge of DevOps/DataOps practices including CI/CD, infrastructure as code (Terraform, CloudFormation), and containerization (Docker, Kubernetes) * Experience with real-time streaming ...

Dlapiper

Data Engineer

San Diego, CA · Hybrid

$121K - $146K/yr

... DataOps concepts and operating in cross-functional teams that include data engineering personas. * The measures of success for this role include delivering data pipelines with trusted, quality data ...

Dlapiper

Data Engineer

San Francisco, CA · On-site

$134K - $162K/yr

... DataOps concepts and operating in cross-functional teams that include data engineering personas. * The measures of success for this role include delivering data pipelines with trusted, quality data ...

Dlapiper

Data Engineer

San Francisco, CA · Hybrid

$134K - $162K/yr

... DataOps concepts and operating in cross-functional teams that include data engineering personas. * The measures of success for this role include delivering data pipelines with trusted, quality data ...

Dlapiper

Data Engineer

San Diego, CA · On-site

$121K - $146K/yr

... DataOps concepts and operating in cross-functional teams that include data engineering personas. * The measures of success for this role include delivering data pipelines with trusted, quality data ...

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Dataops Engineer information

What is a DataOps engineer?

A DataOps Engineer is responsible for streamlining and automating data workflows, ensuring data quality, and enabling efficient data integration across platforms. They work closely with data scientists, analysts, and engineers to implement CI/CD pipelines, manage data infrastructure, and optimize data delivery processes. Their role involves leveraging tools for orchestration, monitoring, and version control to enhance collaboration and reliability in data operations.

What are the common day-to-day responsibilities of a DataOps engineer?

A Dataops Engineer is typically responsible for designing, deploying, and maintaining automated data pipelines that support business analytics and operations. Daily tasks often include monitoring data workflows, troubleshooting pipeline issues, optimizing system performance, and collaborating with data scientists, analysts, and DevOps teams to ensure seamless data delivery. You may also be involved in implementing data quality checks, managing cloud resources, and improving deployment processes. This role is dynamic and fast-paced, requiring both technical expertise and effective cross-team communication. Working as a Dataops Engineer provides the opportunity to work on cutting-edge projects and directly influence data-driven decision-making across the organization.

What are the key skills and qualifications needed to thrive in the DataOps engineer position, and why are they important?

To thrive as a Dataops Engineer, you need a strong background in data engineering, automation, CI/CD practices, and cloud platforms, typically supported by a degree in computer science or a related field. Familiarity with tools like Jenkins, Docker, Kubernetes, Terraform, and major cloud providers (AWS, Azure, GCP) as well as relevant certifications significantly enhances effectiveness in this role. Strong problem-solving skills, collaboration, and clear communication are essential soft skills for working across teams and addressing fast-changing data needs. These combined abilities ensure smooth data pipeline operations, minimize downtime, and enable efficient, reliable delivery of data-driven solutions.

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

The most popular types of Dataops Engineer jobs in California are:

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

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

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

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

Dataops Engineer jobs near you
Infographic showing various Dataops Engineer job openings in California as of August 2026, with employment types broken down into 87% Full Time, 8% Part Time, and 5% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution.

AWS Data Engineer

San Francisco, CA • On-site

Marencor
See more jobs at Marencorexternal

$134K - $162K/yr

Contractor

Re-posted 17 days ago

Job description

Role: AWS Data Engineer (Python, Dataiku) 

Location: SFO, CA – Hybrid

Job Brief

 As an AWS Data Engineer, your role will be to design, develop, and maintain scalable data pipelines on AWS. You will work closely with technical analysts, client stakeholders, data scientists, and other team members to ensure data quality and integrity while optimizing data storage solutions for performance and cost-efficiency. This role requires leveraging AWS native technologies and Databricks for data transformations and scalable data processing.

Responsibilities

  • Lead and support the delivery of data platform modernization projects.
  • Design and develop robust and scalable data pipelines leveraging AWS native services.
  • Optimize ETL processes, ensuring efficient data transformation.
  • Migrate workflows from on-premise to AWS cloud, ensuring data quality and consistency.
  • Design automations and integrations to resolve data inconsistencies and quality issues 
  • Perform system testing and validation to ensure successful integration and functionality.
  • Implement security and compliance controls in the cloud environment.
  • Ensure data quality pre- and post-migration through validation checks and addressing issues regarding completeness, consistency, and accuracy of data sets.
  • Collaborate with data architects and lead developers to identify and document manual data movement workflows and design automation strategies.

 

Skills and Requirements

  • 7+ years of experience with a core data engineering skillset leveraging AWS native technologies (AWS Glue, Python, Snowflake, S3, Redshift).
  • Experience in the design and development of robust and scalable data pipelines leveraging AWS native services.
  • Proficiency in leveraging Snowflake for data transformations, optimization of ETL pipelines, and scalable data processing.
  • Experience with streaming and batch data pipeline/engineering architectures.
  • Familiarity with DataOps concepts and tooling for source control and setting up CI/CD pipelines on AWS.
  • Hands-on experience with Databricks and a willingness to grow capabilities.
  • Experience with data engineering and storage solutions (AWS Glue, EMR, Lambda, Redshift, S3).
  • Strong problem-solving and analytical skills.
  • Knowledge of Dataiku is needed
  • Graduate/Post-Graduate degree in Computer Science or a related field.