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Data Operations Manager Jobs in California (NOW HIRING)

Source, evaluate, and manage relationships with external data labeling vendors, from initial ... operations, training data, or data labeling programs with direct experience managing external ...

AI Data Operations Lead

Milpitas, CA · On-site

$145K - $205K/yr

Drive program execution, resolve blockers, manage priorities, and continuously improve operational efficiency. * Own end-to-end execution of robot data collection and annotation programs, including ...

Drive program execution, resolve blockers, manage priorities, and continuously improve operational efficiency. * Own end-to-end execution of robot data collection and annotation programs, including ...

Description Apple's ML Data Operations group is seeking a Data Operations Engineer to support ... Hands-on familiarity with ML data pipelines, annotation tools, or dataset management practices.

Senior Data Operations Analyst

San Diego, CA · On-site

$91K - $115K/yr

Partner day-to-day with Data Engineering, drafting well-formed requests for durable, managed data sources where long-term gaps exist. Fleet & Performance Analysis * Work directly with operational and ...

Hands-on familiarity with ML data pipelines, annotation tools, or dataset management practices ... Operations, or equivalent combination of education and relevant experience. Experience supporting ...

Senior Data Operations Analyst

San Diego, CA · On-site

$91K - $115K/yr

Partner day-to-day with Data Engineering, drafting well-formed requests for durable, managed data sources where long-term gaps exist. Fleet & Performance Analysis * Work directly with operational and ...

Showing results 21-40

Data Operations Manager information

See California salary details

$30.6K

$95.9K

$169.7K

How much do data operations manager jobs pay per year?

As of Aug 6, 2026, the average yearly pay for data operations manager in California is $95,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,100.00 and $123,900.00 per year, depending on experience, location, and employer.

What are the typical daily responsibilities of a data operations manager?

A Data Operations Manager’s daily responsibilities often include overseeing the flow of data across systems, ensuring high data quality and security, and coordinating the activities of data analysts and engineers. They are responsible for developing and optimizing data processes, monitoring system performance, troubleshooting operational issues, and implementing data governance policies. Collaboration is key, as they frequently work with IT teams, business analysts, and stakeholders to ensure data needs and compliance standards are met. This role requires balancing strategic planning with hands-on management of day-to-day data operations.

What are the key skills and qualifications needed to thrive in the data operations manager position, and why are they important?

To thrive as a Data Operations Manager, you need expertise in data management, analytics, workflow optimization, and a strong background in data governance, commonly backed by a degree in computer science or a related field. Proficiency with data warehousing solutions, ETL tools, SQL, and platforms like Tableau or Power BI, along with familiarity with industry certifications such as CDMP or PMP, is highly valuable. Strong leadership, problem-solving, and organizational skills enable effective collaboration with cross-functional teams and the ability to manage complex data projects. These skills and attributes are crucial for ensuring data quality, streamlining operations, and supporting business decision-making through accurate and timely data management.

Is data operations manager a high paying job?

Data Operations Managers typically earn above-average salaries compared to many other roles in data management and operations. Compensation varies based on experience, industry, and location, but it generally includes a competitive base salary and benefits. Advanced skills in data systems, analytics tools, and leadership can further increase earning potential.

What is a data operations manager?

A Data Operations Manager oversees the processes and systems that manage an organization's data to ensure accuracy, efficiency, and accessibility. They collaborate with data engineers, analysts, and IT teams to improve data workflows, maintain data integrity, and optimize data governance. Their responsibilities often include automating data processes, troubleshooting issues, and ensuring compliance with data policies. This role is critical for organizations that rely on data-driven decision-making and operational efficiency.

What are the most commonly searched types of Data Operations jobs in California? The most popular types of Data Operations jobs in California are:
What are popular job titles related to Data Operations Manager jobs in California? For Data Operations Manager jobs in California, the most frequently searched job titles are:
What cities in California are hiring for Data Operations Manager jobs? Cities in California with the most Data Operations Manager job openings:
Infographic showing various Data Operations Manager job openings in California as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $95,873 per year, or $46.1 per hour.

Human Data Operations Strategist

Encord

San Francisco, CA • On-site

Full-time

Medical, Dental, Vision, PTO

Re-posted 16 days ago


Job description

About us

Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production.

 

Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more. We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator.

 

The role

As a Human Data Operations Strategist, you will play a critical role in managing and optimising data annotation and machine learning workflows for our clients. You will work closely with cross-functional teams, including clients, annotation specialists, and machine learning engineers, to ensure high-quality data is available for AI models.

What you'll do

  • Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams

  • Ensure the highest standards of data quality by designing and refining annotation processes, auditing results, and implementing feedback loops

  • Act as a trusted advisor to clients, helping them design and implement the best data annotation workflow for their human annotation process

  • Provide guidance and feedback to the annotation team, ensuring team members are equipped with the context and skills needed to perform high-quality work aligned with project requirements and best practices

  • Work closely with product and engineering teams to drive improvements in AI training data processes, tools, and methodologies

Who we're looking for

  • A sharp, execution-oriented operator with a consulting or AI company pedigree — you bring structured thinking, strong project management instincts, and a bias for getting things done

  • Analytically rigorous and comfortable with ambiguity — you break down complex operational challenges from first principles and build clear, actionable plans to solve them

  • Technically fluent enough to get hands-on with data — whether that's querying a database, auditing annotation outputs, or automating a workflow in Python

  • Passionate about AI and machine learning, with genuine curiosity about how data quality and operations underpin model performance

  • A natural communicator who can translate fluidly between ML engineers and non-technical clients, keeping complex multi-stakeholder projects on track

  • Entrepreneurial and collaborative — you thrive in fast-paced environments and take ownership without waiting to be told what to do

Experience requirements

  • 3–7 years of professional experience, with a strong preference for backgrounds in top-tier strategy consulting and/or operations or data roles at leading AI or technology companies

  • Proven ability to own complex, multi-stakeholder workflows end-to-end — from scoping and planning through execution, quality assurance, and iteration

  • Working proficiency in Python or SQL, with the ability to query data, automate workflows, or audit annotation outputs; broader familiarity with relational databases or data annotation tooling equally valued

  • Experience designing or optimising data operations processes with a strong eye for quality, consistency, and scalability — ideally in a context involving human-in-the-loop workflows or structured labelling tasks

  • Demonstrated ability to engage effectively with both technical stakeholders (ML engineers, data scientists) and non-technical clients, translating requirements clearly in both directions

  • Bonus: hands-on experience with computer vision, generative AI, or multimodal data workflows; prior exposure to data annotation platforms or quality management frameworks; experience coaching or managing operational teams

Why Encord

  • Competitive salary, commission, and meaningful equity in a high-growth start-up

  • Clear, accelerated growth opportunities as the company scales rapidly

  • Strong in-person culture: 4 days/week

  • Flexible PTO to fully recharge

  • Annual learning & development budget

  • Comprehensive health, dental, and vision coverage

  • Frequent travel opportunities across the U.S., London, and Europe

  • Bi-annual company offsites, twice-weekly team lunches, and monthly socials