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Data Management Executive Jobs in California (NOW HIRING)

... through the CEO. Two things make this role unusual. First, this is as much an operating ... or product data, CRM and billing. • Evaluate the existing data foundation, identify what is ...

... through the CEO. Two things make this role unusual. First, this is as much an operating ... or product data, CRM and billing. • Evaluate the existing data foundation, identify what is ...

... through the CEO. Two things make this role unusual. First, this is as much an operating ... or product data, CRM and billing. • Evaluate the existing data foundation, identify what is ...

... through the CEO. Two things make this role unusual. First, this is as much an operating ... or product data, CRM and billing. • Evaluate the existing data foundation, identify what is ...

... through the CEO. Two things make this role unusual. First, this is as much an operating ... or product data, CRM and billing. • Evaluate the existing data foundation, identify what is ...

... through the CEO. Two things make this role unusual. First, this is as much an operating ... or product data, CRM and billing. • Evaluate the existing data foundation, identify what is ...

... through the CEO. Two things make this role unusual. First, this is as much an operating ... or product data, CRM and billing. • Evaluate the existing data foundation, identify what is ...

... through the CEO. Two things make this role unusual. First, this is as much an operating ... or product data, CRM and billing. • Evaluate the existing data foundation, identify what is ...

... through the CEO. Two things make this role unusual. First, this is as much an operating ... or product data, CRM and billing. • Evaluate the existing data foundation, identify what is ...

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Showing results 1-20

Data Management Executive information

See California salary details

$26.2K

$92.3K

$181.6K

How much do data management executive jobs pay per year?

As of Aug 24, 2026, the average yearly pay for data management executive in California is $92,327.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,200.00 and $118,900.00 per year, depending on experience, location, and employer.

What is a data management executive?

Data Management Executives are professionals responsible for overseeing an organization's data strategy, management, and governance. They ensure that data is collected, stored, protected, and utilized efficiently and securely. Their role often involves developing policies, ensuring regulatory compliance, and leading teams to maximize the value of organizational data. Data Management Executives work closely with IT, business units, and compliance teams to ensure data quality and support decision-making processes.

How does a data management executive typically collaborate with other departments within an organization?

A Data Management Executive works closely with various departments such as IT, compliance, operations, and business analytics to ensure that data is accurate, accessible, and secure. They often lead cross-functional meetings to align data strategies with business goals and oversee the implementation of data governance policies. Effective collaboration is essential, as the role requires gathering input from stakeholders to standardize data processes, resolve data quality issues, and support organizational decision-making with reliable information.

What are the key skills and qualifications needed to thrive as a data management executive, and why are they important?

To excel as a Data Management Executive, you need expertise in data governance, database management, and analytics, often supported by a degree in computer science or information management. Familiarity with tools such as SQL, data warehousing platforms, data visualization software, and certifications like CDMP or DAMA are frequently required. Strong leadership, problem-solving, and communication skills are vital for managing teams and collaborating with stakeholders. These capabilities ensure effective data strategy implementation, regulatory compliance, and the delivery of actionable insights for organizational success.

What is the difference between Data Management Executive vs Data Analyst?

AspectData Management ExecutiveData Analyst
Required CredentialsBachelor's degree in IT, Computer Science, or related field; certifications like CDMP are commonBachelor's degree in Statistics, Mathematics, or related field; certifications like CAP or Microsoft Data Analyst are common
Work EnvironmentCorporate settings, data management teams, IT departmentsBusiness units, analytics teams, consulting firms
Employer & Industry UsageUsed across industries for data governance, quality, and managementUsed across industries for data analysis, reporting, and insights

The Data Management Executive focuses on overseeing data governance, quality, and management strategies within organizations, ensuring data integrity and compliance. In contrast, a Data Analyst primarily interprets data, creates reports, and provides insights to support business decisions. While both roles require strong analytical skills, the Data Management Executive emphasizes data policies and infrastructure, whereas the Data Analyst emphasizes data interpretation and visualization.

Is data management in demand?

Data management executives are in high demand across industries due to the increasing reliance on data-driven decision making. Organizations seek professionals skilled in data governance, database tools, and analytics to ensure data accuracy, security, and compliance, making this a growing field with strong job prospects.

What are the most commonly searched types of Data Management jobs in California?

The most popular types of Data Management jobs in California are:

What cities in California are hiring for Data Management Executive jobs?

Cities in California with the most Data Management Executive job openings:

Infographic showing various Data Management Executive job openings in California as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, 2% Temporary, and 2% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $92,327 per year, or $44.4 per hour.

Head of Data Management

Frederick Fox

Sonoma, CA • On-site

Other

Posted 12 days ago


Job description

Head of Data Strategy & Operational Intelligence


This is a true 0-to-1 mandate at a fast-scaling, profitable SaaS fintech. You will build the operating data foundation that determines how the company defines, measures and trusts performance.

Many critical metrics today depend on manual, human-owned processes and competing definitions. You will establish canonical KPIs, decision rights, governance and an operating rhythm that create one trusted source for leaders across the company, from operating teams through the CEO.


Two things make this role unusual.


First, this is as much an operating-transformation role as it is a data-leadership role. The challenge is not only building pipelines. It is aligning finance, sales, product and operations on what “customer,” “revenue” and other core measures mean, then establishing governance that holds when stakeholders disagree.


Second, the mandate starts with a team at zero. You will hire and develop a small, senior group of data, analytics and software engineers capable of delivering company-wide impact without building a large organization.


What you will own:


• Map the company’s current KPIs, definitions, sources, owners and manual processes.

• Set the company-wide data and operational-intelligence strategy, including a multi-quarter roadmap across several business domains.

• Establish canonical metric definitions, clear decision rights and governance that prevents competing versions of the truth.

• Reconcile systems that describe customers and revenue differently, including transactional or product data, CRM and billing.

• Evaluate the existing data foundation, identify what is missing and make thoughtful build-versus-buy decisions involving governance, semantic layers, modern analytics products and AI-enabled tools.

• Drive adoption across business and engineering teams, including when priorities compete or stakeholders disagree.

• Design the organization, determine the hiring sequence and recruit and develop the team from the ground up.


You may be a strong fit if:


• You have led a company-wide data transformation in a post-product-market-fit business, taking it from strategy through implementation and durable adoption.

• You have owned what a metric means, not only how it is calculated or displayed. You have arbitrated competing definitions and created governance that made one trusted definition stick.

• You have built a multi-quarter roadmap across several business domains and can explain what you prioritized, what you deferred and why.

• You have deeply reconciled at least one or two of the following: product or transactional data, CRM and billing. Depth in two matters more than light exposure to all three.

• You have influenced C-suite decisions and carried a company-level program through competing priorities or executive resistance.

• You have personally designed, hired and developed a technical data organization. You can describe your first hires, the bar you set and people who grew under your leadership.

• You can move from an executive conversation about company strategy into the mechanisms behind data architecture, metric governance and tool selection.

• You have practical, recent experience evaluating or adopting modern analytics and AI-enabled tools. You have a grounded point of view on where they create value, where they do not and how their quality should be measured.

• You are motivated by company-wide impact and ownership rather than by the number of people reporting to you.


Experience in fintech or another regulated, high-stakes data environment such as healthcare, insurance or financial services is strongly preferred.


This role is likely not the right fit if:


• Your experience is primarily building data platforms or infrastructure without owning the business operating model built on top of them.

• You think of yourself primarily as a BI, reporting or dashboarding leader. A separate team owns those capabilities.

• Your leadership experience is still predominantly individual-contributor work.