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Data Operations Jobs in California (NOW HIRING)

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 ...

Data Labeling Operations: Manage the human element of our agentic stack across voice, reasoning and coding agents. You will own the coordination of in-house labelers and external agencies to ensure ...

AI Data Operations Lead

San Jose, CA · Hybrid

$175K - $200K/yr

We are looking for an AI Data Operations Lead to join Figure's Operations org and own a meaningful slice of how we produce human data for our humanoid robots. Data is one of the largest and most ...

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Data Operations information

See California salary details

$51.3K

$126.8K

$197.4K

How much do data operations jobs pay per year?

As of Jul 16, 2026, the average yearly pay for data operations in California is $126,843.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,800.00 and $161,400.00 per year, depending on experience, location, and employer.

Is data operations a good job?

Data operations is a growing field that involves managing, processing, and maintaining data systems to support business functions. It often requires skills in database management, data quality, and tools like SQL or data pipelines, and can offer stable employment with opportunities for advancement. The role is suitable for individuals interested in technology, data analysis, and operational efficiency.

What is a Data Operations job?

A Data Operations job involves managing and optimizing the processes, tools, and workflows that ensure the efficient movement, storage, and accessibility of data. This includes data ingestion, transformation, quality assurance, and pipeline monitoring to support analytics and business intelligence. Data Operations professionals collaborate with engineers, analysts, and business teams to improve data reliability, scalability, and performance. Their role is critical in maintaining clean, accessible, and well-governed data for decision-making.

What is the role of data operations?

Data operations involve managing, processing, and maintaining data to ensure its accuracy, availability, and security for organizational use. Professionals in this field often work with data management tools, databases, and automation processes to support data-driven decision-making.

What is the highest paying data job?

The highest paying data job is typically a Data Engineering Manager or Chief Data Officer, with salaries often exceeding $150,000 annually depending on experience and location. These roles require advanced skills in data architecture, leadership, and often certifications in cloud platforms or data management tools.

Is 30 too late for data science?

Data operations roles often value skills and experience over age, and many professionals transition into data science at various ages, including in their 30s. Building relevant skills such as programming, statistics, and tools like SQL or Python can facilitate entry, regardless of age. Continuous learning and practical experience are key factors for success in data science careers.

What types of teams and departments does Data Operations typically collaborate with?

Data Operations professionals often work closely with data engineering, business intelligence, IT, and analytics teams, as well as stakeholders from various business units such as marketing, finance, and operations. Their role frequently involves coordinating data pipelines, troubleshooting data quality issues, and ensuring smooth integration across systems. This cross-functional collaboration helps align data efforts with organizational goals and supports informed decision-making throughout the company. Being adaptable and communicative is key, as you'll regularly facilitate the flow of data and insights between technical teams and business users.

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

To thrive in Data Operations, you need strong analytical skills, data management experience, and a background in fields like information systems, computer science, or statistics. Familiarity with data visualization tools (e.g., Tableau), database management systems (e.g., SQL), and data integration platforms, along with relevant certifications such as AWS or Microsoft Azure Data Engineer, are highly valuable. Exceptional attention to detail, problem-solving ability, and effective collaboration skills differentiate top performers in this role. These competencies ensure accurate data flow, system integrity, and seamless cross-team cooperation, all of which are critical for maintaining reliable business operations.

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 cities in California are hiring for Data Operations jobs? Cities in California with the most Data Operations job openings:

Human Data Operations Strategist

Encord

San Francisco, CA • On-site

$130K - $210K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 25 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: 3–5 days/week in our newly launched North Beach loft office

  • Flexible PTO to fully recharge

  • 18 paid vacation days in the U.S. plus federal holidays

  • 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

Compensation Range: $130K - $210K