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Data Ops Engineer Jobs in California (NOW HIRING)

Senior Staff ML Ops Engineer

Santa Clara, CA · On-site

$121K - $167K/yr

The Senior Staff ML Ops Engineer will partner closely with data scientists, algorithm developers, infrastructure teams, product leaders, and cross-functional stakeholders to accelerate the deployment ...

Senior Staff ML Ops Engineer

Santa Clara, CA · On-site

$121K - $167K/yr

The Senior Staff ML Ops Engineer will partner closely with data scientists, algorithm developers, infrastructure teams, product leaders, and cross-functional stakeholders to accelerate the deployment ...

Familiarity with data engineering tools (e.g., Airflow, Spark) and ML Ops frameworks. * Solid understanding of software engineering principles and DevOps practices. * Ability to communicate complex ...

Familiarity with data engineering tools (e.g., Airflow, Spark) and ML Ops frameworks. * Solid understanding of software engineering principles and DevOps practices. * Ability to communicate complex ...

Dev Ops Engineer

Downey, CA · On-site

$54.50 - $74.75/hr

Dev Ops Engineer Downey, CA 12+ months Position Description: A DevOps Engineer serves as the ... Have a minimum of seven (7) years of experience in electronic data processing systems study, design ...

Senior AI/ML Ops Engineer Agent Evaluation, Observability & Production Reliability About the Role ... scale Data, AIML capabilities across the organization. Expertise in causal inference and ...

Dev Ops Engineer

San Francisco, CA · On-site

$200K - $300K/yr

We are looking to hire a Dev Ops Engineer for our Software Team. What You'll Do: * Own the ... Own cloud infrastructure for training, data processing, and remote services * Partner closely with ...

Senior Staff ML Ops Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

The Senior Staff ML Ops Engineer will partner closely with data scientists, algorithm developers, infrastructure teams, product leaders, and cross-functional stakeholders to accelerate the deployment ...

Senior Staff ML Ops Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

The Senior Staff ML Ops Engineer will partner closely with data scientists, algorithm developers, infrastructure teams, product leaders, and cross-functional stakeholders to accelerate the deployment ...

... ops for the data platform. Work with engineering to ship tooling improvements, track operational metrics, and identify gaps • Create documentation, SOPs, and training materials for operational ...

Responsibilities : • Build the data and reporting layer of eval ops - such as throughput, success ... Developers • Someone adept at prioritizing competing requests, able to move quickly and in an ...

Sr MLop engineer

San Leandro, CA · On-site

$116K - $159K/yr

Syntricate Technologies is seeking a Sr ML Ops Engineer to drive the full lifecycle of machine learning solutions, bridging the gap between data science model development and production-grade ML Ops ...

Ensure Data Integrity - Maintain high data quality across systems, resolving inconsistencies and ... Cross-Functionally - Work closely with Sales, Marketing, Customer Success, and Engineering to ...

Staff App Ops Engineer

Mountain View, CA · On-site

$202K - $274K/yr

... App Ops Engineer to lead operational excellence and site reliability to deliver the always-on ... Architect cloud-native data systems - design highly available, secure, performant infrastructure at ...

Staff App Ops Engineer

Mountain View, CA · On-site

$202K - $274K/yr

... App Ops Engineer to lead operational excellence and site reliability to deliver the always-on ... Architect cloud-native data systems - design highly available, secure, performant infrastructure at ...

Senior ML Ops Engineer

El Segundo, CA · On-site

$150 - $240/hr

HIPAA and SOC 2 across pipelines, with sound PHI handling in training data, artifacts, and outputs ... Ops Engineer, you will be employed by Circadia Health, Inc. The anticipated annual base salary ...

... App Ops Engineer to lead operational excellence and site reliability to deliver the always-on ... Architect cloud-native data systems -- design highly available, secure, performant infrastructure ...

Showing results 21-40

Data Ops Engineer information

See California salary details

$43.9K

$128K

$175.2K

How much do data ops engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data ops engineer in California is $128,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $135,700.00 per year, depending on experience, location, and employer.

What is a Data Ops Engineer?

Data Ops Engineers are professionals who bridge the gap between data engineering and operations. They focus on automating, monitoring, and optimizing data pipelines to ensure reliable, efficient, and secure data flow within organizations. Their responsibilities often include managing data integration, workflow orchestration, deployment of data infrastructure, and implementing best practices for data quality and governance. Data Ops Engineers work closely with data scientists, analysts, and IT teams to support data-driven decision-making and maintain high data availability. Their role is crucial in modern organizations that rely on large-scale data processing and analytics.

How does a Data Ops Engineer typically collaborate with data scientists and software engineers within an organization?

Data Ops Engineers play a crucial role in bridging the gap between data science and engineering teams. They ensure smooth data pipeline operations, help automate workflows, and support data scientists by providing reliable, scalable infrastructure. Collaboration often involves participating in cross-functional meetings to understand data requirements, troubleshooting data quality issues, and implementing solutions that enable efficient experimentation and model deployment. This collaborative environment helps facilitate quick iterations and reliable delivery of data products.

What are the key skills and qualifications needed to thrive as a Data Ops Engineer, and why are they important?

To thrive as a Data Ops Engineer, you need a solid background in data engineering, automation, and cloud infrastructure, often supported by a degree in computer science or related field. Experience with tools like Apache Airflow, Docker, Kubernetes, CI/CD pipelines, and proficiency in scripting languages such as Python or Bash is typically required. Strong problem-solving skills, attention to detail, and effective communication help you collaborate with data teams and troubleshoot complex data workflows. These skills ensure reliable data delivery, streamlined operations, and scalable solutions that support organizational data goals.

What is the difference between Data Ops Engineer vs Data Engineer?

AspectData Ops EngineerData Engineer
CredentialsCertifications in data management, cloud platforms, scriptingCertifications in data engineering, SQL, cloud services
Work EnvironmentFocus on data pipelines, automation, deployment, and monitoringFocus on data modeling, ETL processes, database design
Industry UsageUsed in organizations emphasizing data operations, automation, and DevOps practicesUsed in data-centric roles focusing on building data infrastructure

While both roles work with data infrastructure, Data Ops Engineers primarily focus on automating and managing data pipelines and deployment processes, whereas Data Engineers concentrate on designing and building data systems. The roles often overlap but differ in their core focus areas and responsibilities.

Is data operations a good career?

Data Operations, often involving roles like Data Ops Engineer, is a growing field focused on managing data pipelines, automation, and infrastructure. It offers strong job demand, competitive salaries, and opportunities to work with tools like cloud platforms and data management systems, making it a viable career choice for those interested in data and technology.

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

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

Infographic showing various Data Ops Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $128,018 per year, or $61.5 per hour.

DBT/Snowflake/Azure Data Engineer w/ Retail Experience

3B Staffing LLC

Pleasanton, CA • Hybrid

$127K - $152K/yr

Contractor

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Candidates must be able to convert fte without sponsorship now or at any point in the future

Hybrid in Pleasanton, CA (ONSITE 3x a week)

Okay for relocation- but need to start day 1 in CA

3 month+ contract to hire

Will be Onshore Lead for 2 Teams- Supply Chain and Merchandising

12- 15 years exp

Architect or Senior Engineer but they will be doing development work

Hands on exp- not looking for manager

Cloud data warehousing

Snowflake

Azure

Aws GCP is secondary- Snowflake is primary

Python, SQL

DBT Experience

Previous retail (Prev Albertsons would be great!)

Communication is key, speaking to stakeholders

Will need to present to leadership

Python sql technical round

Ask to provide how code works, how do you want to do this

Snowflake

Communication skills, explain implementation teams

Strong communication

Communication skills

Everyone's resume says every cloud

Relocation

Interview Process:

45 min with Manager

1 hour technical round sr data engineer

Leadership round with Manager and VP

Work with functionally split within retail analytics side

Person would be working on hub and spoke model- supply chain and merchandising

Two domains supply chains and store sites- lead engineers do review to other on team

GENERAL PURPOSE:

Briefly summarize the overall purpose of the position. This is a short explanation of the job's primary purpose and functions.

The Data Engineer III plays a critical role in engineering of data solutions that support Ross reporting and analytic needs. As a key member of the Data engineering team, will work on diverse data technologies such as Steramsets, dbt, data ops and others to build insightful, scalable, and robust data pipelines that feed our various analytics platforms.

ESSENTIAL FUNCTIONS:

List the core duties or tasks that are fundamental to the performance of the job. This section provides detailed information about the job's tasks, duties, responsibilities, tool and equipment uses. Define the purpose, function and the result to be accomplished. Duties and responsibilities should be listed in order of their importance, occurrence, or time requirements.

  • Design and Model data engineering pipelines that support Ross reporting and analytic needs.
  • Engineer efficient, adaptable, and scalable data pipelines for moving data from different sources into our Cloud Lakehouse
  • Understand and analyze business requirements and translate into well-architected solutions that demonstrate the modern BI & Analytics platform
  • Be a part of data modernization projects providing direction on matters of overall design and technical direction, acts as the primary driver toward establishing guidelines and approaches
  • Develop and deploy performance optimization methodologies
  • Drive timely and proactive issue identification, escalation & resolution
  • Collaborate effectively within Data Technology teams, Business Information teams to design and build optimized data flows from source to Data visualization

QUALIFICATIONS AND SPECIAL SKILLS REQUIRED:

List Education level, Years of Experience, Technical Knowledge, and/or Certifications required for the position.

  • 12 + years in-depth, data engineering experience and execution of data pipelines, data ops, scripting and SQL queries
  • 5+ years proven data architecture experience - must have demonstrable experience data architecture, accountable for data standards, designing data models for data warehousing and modern analytics use-cases (e.g., from operational data store to semantic models)
  • At least 3 years experience in modern data architecture that support advanced analytics including Snowflake, Azure, etc. Experience with Snowflake and other Cloud Data Warehousing / Data Lake preferred
  • Expert in engineering data pipelines using various data technologies - ETL/ELT, big data technologies (Hive, Spark) on large-scale data sets demonstrated through years of experience
  • 5+ years hands on data warehouse design, development, and data modeling best practices for modern data architectures
  • Highly proficient in at least one of these programming languages: Java, Python
  • Experience with modern data modelling tools, data preparation tools
  • Experience with adding data lineage, technical glossary from data pipelines to data catalog tools
  • Highly proficient in Data analysis - analyzing SQL, Python scripts, ETL/ELT transformation scripts
  • Highly skilled in data orchestration with experience in tools like Ctrl-M, Apache Airflow. Hands on DevOps/Data Ops experience required
  • Knowledge/working experience in reporting tools such as MicroStrategy, Power BI would be a plus
  • Self-driven individual with the ability to work independently or as part of a project team
  • Experience working in an Agile Environment preferred, Familiarity with Retail domain preferred
  • Experience with Streamsets, dbt preferred
  • Strong communication skills are required with the ability to give and receive information, explain complex information in simple terms and maintain a strong customer service approach to all users
  • Bachelor's Degree in Computer Science, Information Systems, Engineering, Business Analytics, Business Management required