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Product Manager Data Analytics Jobs in California

... analytical domains while helping evolve the data foundation that powers Windfall's products, AI ... lifecycle management, with success measured through customer impact and product KPIs • ...

As a Senior Product Manager on the Data team, you will partner closely with leaders across ... analytical domains while helping evolve the data foundation that powers Windfall's products, AI ...

We are seeking a Product Manager to support Visa's Master Data Platform within the Global Data ... Gather, analyze, and translate business requirements into well-defined product requirements, user ...

We are seeking a Product Manager to support Visa's Master Data Platform within the Global Data ... Gather, analyze, and translate business requirements into well-defined product requirements, user ...

Data and Analytics_AMER Key Responsibilities: * Help develop compelling "jira stories" and UX that ... Data product management experience with proficiency in building data products, dashboards and ad ...

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Product Manager Data Analytics information

What is a product manager data analytics?

A Product Manager Data Analytics is a professional responsible for overseeing the development, strategy, and success of data analytics products or features within an organization. They work at the intersection of business, technology, and data, collaborating with data scientists, engineers, and stakeholders to define product vision, prioritize features, and ensure analytics solutions meet user and business needs. Their role involves understanding market trends, user requirements, and translating complex data insights into actionable product enhancements. Ultimately, they drive the product lifecycle to deliver value through data-driven decision making.

How does a product manager data analytics typically collaborate with data scientists and engineers on a project?

As a Product Manager in Data Analytics, you serve as the bridge between business stakeholders and technical teams. You'll work closely with data scientists to define project objectives, ensure that analytical models align with business needs, and prioritize features based on user impact. Collaboration with data engineers is essential for understanding data infrastructure requirements and ensuring reliable data pipelines. Regular communication, sprint planning, and joint problem-solving sessions are core to fostering alignment and delivering successful analytics solutions.

What are the key skills and qualifications needed to thrive as a product manager data analytics, and why are they important?

To thrive as a Product Manager in Data Analytics, you need a strong background in data analysis, product lifecycle management, and business strategy, often supported by a degree in business, computer science, or a related field. Familiarity with data visualization tools (like Tableau or Power BI), SQL, and experience with analytics platforms are typically required, and certifications such as Certified Scrum Product Owner (CSPO) can be advantageous. Exceptional communication, problem-solving, and stakeholder management skills help you bridge technical teams and business objectives. These abilities are crucial for delivering data-driven products that meet user needs and provide measurable business value.

What is the difference between Product Manager Data Analytics vs Data Analyst?

AspectProduct Manager Data AnalyticsData Analyst
Primary FocusOverseeing data-driven product strategies and roadmapsAnalyzing data to generate reports and insights
Skills & CertificationsProduct management, data analytics, SQL, communicationData analysis, SQL, Excel, visualization tools
Work EnvironmentCross-functional teams, product development cyclesData teams, business units, reporting environments
Industry UsageTech, e-commerce, SaaS companiesFinance, marketing, healthcare, tech

Product Manager Data Analytics focuses on guiding product strategies using data insights, while Data Analysts primarily analyze data to produce reports. Both roles require analytical skills and familiarity with data tools, but their responsibilities and scope differ significantly.

Do product managers do data analysis?

Product managers often perform data analysis to inform product decisions, track performance metrics, and understand user behavior. They use tools like SQL, Excel, or analytics platforms to interpret data and prioritize features, but they typically collaborate with data analysts or data scientists for complex analysis. Strong analytical skills are valuable in this role to support data-driven decision-making.

What are popular job titles related to Product Manager Data Analytics jobs in California?

For Product Manager Data Analytics jobs in California, the most frequently searched job titles are:

What job categories do people searching Product Manager Data Analytics jobs in California look for?

The top searched job categories for Product Manager Data Analytics jobs in California are:

What cities in California are hiring for Product Manager Data Analytics jobs?

Cities in California with the most Product Manager Data Analytics job openings:

Infographic showing various Product Manager Data Analytics job openings in California as of August 2026, with employment types broken down into 90% Full Time, 9% Part Time, and 1% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution.

Principal Product Manager, Data

Procore

San Francisco, CA • On-site

Other

Re-posted 28 days ago


Job description

Procore has the richest construction dataset in the industry. We're looking for a Principal Product Manager, Data to lead the work to turn that data into higher-order data products that make construction companies smarter.

As a Principal Product Manager, Data, your job is to define what we build on top of our core data model, combining Procore data with external construction systems, identifying patterns across hundreds of thousands of projects, and defining curated datasets and predictive models that power AI experiences. We expect this person to become the deepest expert at Procore on construction data - how it's generated across the project lifecycle, how it varies across customer types, what it can predict, and where the gaps are.

Procore manages data across millions of construction projects. This role will add value to that data by building products that combine signals across systems, surface patterns customers can't see today, and turn historical data into forward-looking intelligence.

This role reports to the Senior Director, Data Products and is based in our San Francisco office, supporting Procore's Datagrid AI Division. Given the collaborative and fast moving nature of this work, we are seeking candidates who are available to work onsite five days per week. This is an immediate opening!

What you'll do:
  • Define and prioritize curated data products that combine signals across Procore's platform into derived datasets that customers and internal products can act on.

  • Identify opportunities for predictive models that turn historical construction data into forward-looking intelligence. Define the data requirements, success criteria, and business cases for each.

  • Own the strategy for how Procore data combines with external construction system data to create a more complete picture of project and portfolio performance.

  • Work closely with the teams that own Procore's core data model to ensure curated products are well-grounded in the underlying entities and relationships.

  • Define data quality, completeness, and validation criteria for derived datasets. Understand what "good data" looks like across different customer configurations and tool adoption levels.

  • Partner with product teams across Procore to understand what data products would unlock the most value for analytics, insights, and AI experiences.

  • Own APIs and data services that make curated data products available to consuming products and experiences across Procore.

  • Make prioritization calls on which data products to invest in next based on customer value and product impact.

  • Lead cross-functional collaboration with Engineering, Data Science, Data Engineering, and Go-to-Market teams through all phases of product development.

  • Define and track success metrics for data product adoption and business impact across Procore's product portfolio.

  • Leverage generative tools and agentic workflows to move faster and work smarter

What we're looking for:
  • 5+ years of product management or equivalent relevant experience with meaningful time spent on data products, data platforms, analytics infrastructure, or ML/AI products in B2B SaaS.

  • Experience defining derived data products or curated datasets - you've taken raw platform data and turned it into something more valuable than the sum of its parts.

  • Deep understanding of data modeling concepts - entity-relationship design, semantic models, API design, and the tradeoffs between flexibility and structure. You need to understand a core data model well enough to build confidently on top of it. Experience with cross-system data a plus.

  • Ability to take large, complex strategic problems and break them into logical intermediate steps that deliver consistent value.

  • Track record of working across many teams without direct authority. You'll need to build relationships, create buy-in, and resolve conflicts when teams have competing data needs.

  • Comfort with ambiguity at scale. The construction industry has thousands of workflows across general contractors, specialty contractors, and owners. There is no single "right" way to model derived data - you'll need to make defensible tradeoffs and own them.

  • Strong enough technically to review data model designs, evaluate API contracts, and have credible conversations with data engineers and backend engineers. You should be able to look at a dataset and spot what's missing.

  • Construction industry experience is a strong plus. You'll need to understand why a change event becomes a commitment change order, why budget line items are planned spend and not actual cost, and why WBS codes matter. If you don't have this background, you need the curiosity and speed to learn a complex domain quickly.

  • Demonstrated ability to define initiative-level customer and business outcomes, track progress against them, and explain why they're meaningful.

  • Excited to use AI tools to multiply what you and your team can do.

  • Excellent written and verbal communication.

Additional Information

Base Pay Range:

227,976.00 - 313,467.00 USD Annual

This role may also be eligible for Equity Compensation and/or Bonus Incentive Compensation. Procore is committed to offering competitive, fair, and commensurate compensation. Actual compensation will be based on a candidate's job-related skills, experience, education or training, and location.

For Los Angeles County (unincorporated) Candidates:

Procore will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable federal, state, and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.

A criminal history may have a direct, adverse, and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: 1. appropriately managing, accessing, and handling confidential information including proprietary and trade secret information, as well as accessing Procore's information technology systems and platforms; 2. interacting with and occasionally having unsupervised contact with internal/external customers, stakeholders, and/or colleagues; and 3. exercising sound judgment.