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Flexible Data Product Manager Jobs (NOW HIRING)

Join Vanguard's IT Data & Analytics organization as a Data Product Manager, where you will own and drive the strategy, delivery, and adoption of enterprise data products that enable decisionโ€‘making ...

Senior Data Product Manager

San Jose, CA

$148K - $195K/yr

As a Senior Data Product Manager, you'll be at the forefront of transforming data into actionable insights for our innovative Firefly platform. This is your chance to work with a world-class team and ...

Prior work experience in data product management preferred. Job Expectations Operate customary equipment and technology used in a business environment, with or without accommodation. Note: This ...

The Master Data Product Manager translates customer needs into system features and manages their development. The incumbent oversees the day-to-day management of Product Master Data products and ...

We are looking for a Product Manager to join our Product team to own and grow a data domain ... Flexible PTO and 10 paid holidays * Flexible work hours * Paid leave programs * Marketplace for ...

Showing results 21-40

Flexible Data Product Manager information

See salary details

$51.5K

$159.4K

$197K

How much do flexible data product manager jobs pay per year?

As of Aug 6, 2026, the average yearly pay for flexible data product manager in the United States is $159,405.00, according to ZipRecruiter salary data. Most workers in this role earn between $141,000.00 and $197,000.00 per year, depending on experience, location, and employer.

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

AspectFlexible Data Product ManagerData Analyst
Required CredentialsBachelor's or higher in CS, Data Science, or related; experience in product managementBachelor's in Statistics, Data Science, or related; proficiency in data analysis tools
Work EnvironmentCross-functional teams, product development, strategic planningData reporting, visualization, data cleaning, and analysis
Employer & Industry UsageTech companies, e-commerce, finance, healthcareBusiness intelligence, marketing, finance, research

The Flexible Data Product Manager focuses on developing data-driven products, managing cross-functional teams, and aligning data initiatives with business goals. In contrast, a Data Analyst primarily interprets data, creates reports, and provides insights. While both roles require strong analytical skills, the product manager emphasizes strategic planning and product lifecycle management, whereas the analyst concentrates on data analysis and visualization.

What cities are hiring for Flexible Data Product Manager jobs? Cities with the most Flexible Data Product Manager job openings:
What are the most commonly searched types of Data Product Manager jobs? The most popular types of Data Product Manager jobs are:
What states have the most Flexible Data Product Manager jobs? States with the most job openings for Flexible Data Product Manager jobs include:

Senior Data Product Manager

Elm Street Technology LLC

Seattle, WA โ€ข On-site

$140K - $180K/yr

Full-time

Re-posted 19 days ago


Job description

Description:Job Summary

This role sits at the intersection of executive strategy and technical implementation, evaluating where we are, identifying the gaps, and charting a course for where we need to go. The SDPM is responsible for designing new customer-facing data products while also ensuring our internal data operations are efficient, reliable, and built to scale.

This role demands genuine expertise in the nuance and complexity of MLS data and a deep understanding of how data moves through the real estate industry.

The SDPM reports directly to the Senior Director of Product and works closely with engineering, data, sales, customer success, and executive leadership.

Key Responsibilities

Data Strategy and Roadmap

  • Evaluate Elm's current data landscape end to end: what we have, how it is being used, and where the gaps are between our current capabilities and what is possible.
  • Develop a prioritized data product roadmap that maps our MLS data assets to high-impact product opportunities, spanning customer-facing tools, market intelligence products, and operational improvements.
  • Stay ahead of where the real estate data industry is heading and bring forward-looking recommendations to product and executive leadership before the market forces our hand.

Data Product Development and Delivery

  • Own the design and delivery of new customer-facing data products, from problem framing and scoping through launch and iteration.
  • Identify the most valuable ways to surface Elm's MLS data for real estate professionals, including pre-listing intelligence, market analytics, listing performance insights, and comparative market tools.
  • Partner closely with engineering and data teams to translate product vision into clear specifications, ensuring the underlying data architecture supports what the product needs to do.
  • Collaborate closely with engineering, data infrastructure, design, sales, and customer success teams to align data product priorities with broader business goals.
  • Establish a repeatable cadence for data product delivery, bringing the same structure and discipline to data product rollout that the PMM brings to feature launches.

MLS Data Expertise and Industry Knowledge

  • Develop and maintain deep expertise in MLS data: how it is structured, how it is licensed, how it flows through the industry, and what compliance and display requirements govern its use.
  • Become Elm's internal authority on IDX, RETS, and RESO standards, and the broader data ecosystem our products depend on.
  • Build and manage relationships with MLS organizations and technology partners to identify opportunities to access, enrich, or commercialize data in ways that benefit our customers.

Internal Data Operations and Efficiency

  • Identify opportunities to improve how Elm processes and manages data internally, including reducing manual effort, improving data quality and response times, and decreasing customer-facing issues tied to data problems.
  • Ensure data quality, lineage, and governance are built into the platform in ways that support both customer-facing products and internal analytics.
  • Bring a product mindset to operational problems, asking not just how we fix an issue but how we design systems that prevent it at scale.
Requirements:Required Skills and Experience:
  • 7+ years of product management experience, with at least 5 years focused on data products, data platforms, or data-intensive applications.
  • Deep, hands-on knowledge of MLS data: IDX, RETS, and RESO standards, compliance requirements, data licensing, display rules, and how listing data flows through the real estate ecosystem. You have built products on top of MLS feeds and understand the nuance.
  • Proven track record of building data products from zero to one, not just maintaining or improving existing features, but creating net-new products that generated measurable business impact.
  • Comfortable partnering with data engineers on schema design, data modeling, and pipeline architecture decisions. You understand how technical choices shape product outcomes.
  • Strong strategic thinking paired with a bias toward execution. You can develop a long-term roadmap and then roll up your sleeves to get the first product shipped.
  • Excellent written and verbal communication skills. You can translate complex data concepts into clear, compelling narratives for non-technical audiences including customers, sales teams, and executive leadership.
  • Experience working cross-functionally in a high-growth environment where alignment requires relationship-building, not authority.
Preferred Skills and Experience:
  • Experience as the first or foundational data product hire at a company. You know what it means to build the function from scratch and have done it before.
  • Familiarity with how AI and machine learning can be applied to data products, including where these tools create genuinely new product capabilities and where they do not. You are comfortable incorporating AI-informed approaches into your product thinking.
  • Experience working with external data partners, including MLS organizations, data vendors, or technology integrators, and managing those relationships to drive product outcomes.
  • Background in real estate, prop-tech, or adjacent industries where data quality and freshness are directly visible to customers.