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Data Operations Lead Jobs in California (NOW HIRING)

Sieve

Data Operations Lead

San Francisco, CA · On-site

The Data Operations Lead will manage the execution and scaling of the company's data operations platform, overseeing workforce management, QA processes, and driving growth initiatives.

Figure

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 ...

Sieve, Inc

Product Operations Lead

San Francisco, CA · On-site

About Us Sieve is the only AI research lab exclusively focused on video data. We combine exabyte ... About the Role As Product Operations Lead, you'll own the day-to-day execution and scaling of Sieve ...

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All JobsData Operations Lead JobsData Operations Lead Jobs in California

Data Operations Lead information

See California salary details

$51.3K

$126.8K

$197.4K

How much do data operations lead jobs pay per year?

As of Jul 15, 2026, the average yearly pay for data operations lead 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.

What jobs pay 200,000 a year in the USA?

In the USA, senior data operations roles such as Data Operations Lead, Data Director, or Chief Data Officer can earn $200,000 or more annually, especially with extensive experience, advanced skills in data management tools, and leadership responsibilities. High-paying roles often require a strong background in data governance, analytics, and relevant certifications, and may be found in large corporations or financial institutions.

What is a Data Operations Lead job?

A Data Operations Lead is responsible for overseeing data workflows, ensuring data accuracy, and optimizing data management processes within an organization. They collaborate with data engineers, analysts, and business teams to streamline data collection, processing, and governance. Their role includes maintaining data pipelines, improving data quality, and ensuring compliance with data security regulations. By implementing best practices and automation, they help improve efficiency and maximize the value of data for decision-making.

What are common challenges faced by a Data Operations Lead, and how can they be addressed?

Data Operations Leads often encounter challenges such as managing large-scale data integration from diverse sources, ensuring data quality and consistency, and automating processes to improve efficiency. These challenges require a proactive approach to troubleshooting, setting robust data governance standards, and collaborating closely with IT, analytics, and business teams. By fostering clear communication, leveraging modern data management tools, and establishing strong protocols, Data Operations Leads can effectively address these issues. This collaborative and strategic mindset ultimately helps organizations maximize the value of their data assets while minimizing operational risks.

What jobs pay $500,000 a year in the US?

High-level executive roles such as CEOs, CFOs, and other C-suite positions often reach or exceed $500,000 annually, especially in large corporations. Certain specialized roles like investment bankers, hedge fund managers, and successful entrepreneurs can also earn this level of income, often supplemented by bonuses, stock options, or profit sharing. Achieving this salary typically requires extensive experience, advanced skills, and significant responsibility.

What does a data operations lead do?

A data operations lead manages the processes and systems that handle data collection, storage, and quality assurance within an organization. They oversee data workflows, coordinate with data teams, and often use tools like SQL, data pipelines, and analytics platforms to ensure data accuracy and accessibility. Strong organizational and technical skills are essential for this role.

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

To thrive as a Data Operations Lead, you need a strong background in data management, analytics, and process optimization, often supported by a degree in computer science, data science, or a related field. Proficiency with database platforms (such as SQL), ETL tools, cloud data services, and familiarity with data governance frameworks and certifications like Certified Data Management Professional (CDMP) are highly valuable. Exceptional leadership, problem-solving abilities, and strong communication skills help in guiding teams and collaborating with stakeholders. These competencies are crucial for maintaining data quality, streamlining operations, and ensuring that data initiatives align with organizational objectives.

What jobs in the US pay 300,000 a year?

For a Data Operations Lead, salaries of $300,000 or more annually are typically found in senior leadership roles such as Director or Vice President of Data, especially in large organizations or tech companies. High compensation may also require advanced skills in data management, analytics, and leadership, along with extensive experience and sometimes specialized certifications. These roles often involve strategic decision-making, managing teams, and overseeing large-scale data initiatives.
What are the most commonly searched types of Data Operations Lead jobs in California? The most popular types of Data Operations Lead jobs in California are:
What are popular job titles related to Data Operations Lead jobs in California? For Data Operations Lead jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Operations Lead jobs in California look for? The top searched job categories for Data Operations Lead jobs in California are:
Data Operations Lead jobs near you
Infographic showing various Data Operations Lead 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 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $126,843 per year, or $61 per hour.
Data Operations Lead

Data Operations Lead

Sieve

San Francisco, CA • On-site

Full-time

Posted 28 days ago

Job description

Job Summary:
Sieve is an AI research lab focused on video data, aiming to solve the bottleneck in the growth of applications powered by high-quality training data. The Data Operations Lead will manage the execution and scaling of the company's data operations platform, overseeing workforce management, QA processes, and driving growth initiatives.
Responsibilities:
• Operate and scale Sieve's internal data ops platform, including workforce management, task assignment, and QA workflows
• Drive platform growth: run acquisition campaigns, test new sourcing channels, and grow the user base through creative and scalable strategies
• Source, onboard, and manage a distributed human workforce for data annotation, curation, and quality review
• Build and improve QA processes to ensure data output meets the standards required by frontier AI labs
• Own product 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 workflows
Qualifications:
Required:
• Mixed technical and non-technical skillset, comfortable with data tooling, light scripting, and spreadsheet-level analysis
• Strong organizational skills and attention to detail; able to manage multiple concurrent work streams
• Growth mindset: experience running or contributing to user acquisition, sourcing campaigns, or platform growth efforts
• Bachelor's degree in CS, STEM, or equivalent practical experience
• In-person at our SF HQ
Preferred:
• Experience managing human-in-the-loop data operations or annotation pipelines
• At least 1 year of engineering experience or strong technical fluency
• Experience as an early hire at a startup or spearheading ops at an AI lab
• Familiarity with data quality frameworks or ML data pipelines
Company:
Sieve supplies video data to frontier AI labs. Founded in 2022, the company is headquartered in San Francisco, USA, with a team of 11-50 employees. The company is currently Early Stage.

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