Senior Product Manager - Technical (Data Product Tooling)

QXO is a leading distributor and installer of building products serving an $800 billion market. The company’s mission is to modernize the building products industry through advanced technology and a best-in-class customer experience. QXO is North America’s largest distributor and installer of insulation, the second-largest distributor of roofing products, the second-largest publicly traded distributor of lumber and building materials, and the largest distributor of waterproofing products. The company is targeting $50 billion in annual revenue within the decade through accretive acquisitions and organic growth. For more information, visit QXO.com.

What you'll do:

As a Senior Product Manager, Technical (Data Product Tooling), you will own the product layer between QXO's lakehouse and the applications that run the business. You will deliver the tooling that makes every data product easy to find, defined once, checked for quality and freshness, and fast and affordable to serve, working with data engineering, data governance, analytics, applied science and platform engineering teams.

Your work will turn a growing set of data products into a trusted foundation for analytics, AI agents, pricing, forecasting and future acquisitions. You will set the standards and build the tools teams use every day, and you will measure success by adoption and trust, not by launches.

Key Responsibilities

• Define the Data Product Tooling Vision: Develop and communicate the vision, strategy and roadmap for the tooling between the lakehouse and product applications.
• Own One Definition per Metric: Lead golden definitions for core entities such as customer, item, branch and sales, and the review and sign-off workflow that keeps every metric defined once.
• Set the Definition of Done for Data Products: Define production ready, including ownership, documentation, contracts, freshness and quality checks, with status visible from the platform.
• Build the Data Catalog and Access Experience: Deliver one place to find, register and request access to data products and metrics, with owner, definition, lineage, freshness and quality for each.
• Drive Serving, Cost and Performance Standards: Partner with engineering on materialization, partitioning and aggregates, plus cost labels and budgets, so analytics and AI workloads stay fast and affordable.
• Make Acquisitions Fast to Integrate: Own the onboarding kit that maps each acquired company's customer, product, pricing and sales data to common definitions.
• Grow Stewardship and Governance: Work with data governance and business owners to name data stewards and keep metadata, definitions and ownership current.
• Data-driven Decision Making: Define success metrics such as certified coverage, conflicting definitions retired, catalog usage and cost per query, and use them to drive the roadmap.

What you'll bring:

Qualifications & Skills

• 6+ years of Technical Product Management experience, with 3+ years on data platforms, data products or analytics infrastructure.
• 3 years of experience taking technical products from 0:1 end to end.
• Proven track record of launching data platform capabilities such as data catalogs, metadata management, semantic or metrics layers, data quality or data observability tools.
• Working knowledge of modern data stacks such as BigQuery, Snowflake or Databricks, dbt and orchestration tools.
• Ability to write SQL and read data models to validate definitions and requirements yourself.
• Experience setting standards across multiple engineering teams and driving adoption without direct authority.
• Strong planning, prioritization, and cross-functional communication skills.
• Bachelor's degree in Computer Science, Engineering, or related technical field, or equivalent practical experience.

Preferred Qualifications

• MBA or an advanced technical degree.
• Experience with data mesh or data as a product operating models, data contracts and federated governance.
• Experience with catalog and governance tools such as OpenMetadata, DataHub, Collibra, Atlan or Dataplex.
• Experience with master data management or entity resolution.
• Experience integrating data from acquisitions, ERP migrations or many source systems into a common model.
• Background in distribution, supply chain, manufacturing or other B2B industries with complex product and customer data.

What you'll earn

• Base pay range: $145,000 - $275,000
• Annual performance bonus
• Long term incentive (equity/stock)
• 401(k) with employer match
• Medical, dental, and vision insurance
• PTO, company holidays, and parental leave
• Paid Time Off/Paid Sick Leave: Applicants can expect to accrue 15 days of paid time off during their first year (4.62 hours for every 80 hours worked) and increased accruals after five years of service.
• Paid training and certifications
• Legal assistance and identity protection
• Pet insurance
• Employee assistance program (EAP)

QXO is an Equal Opportunity Employer. We value diversity and do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, or any other protected status.

To comply with Pay Transparency laws, employers must disclose an annual salary range. Actual offers depend on factors such as location, experience, skills, and market data. This position may also offer variable compensation.

USD $145,000.00 - USD $310,000.00 /Yr.

As a Senior Product Manager, Technical (Data Product Tooling), you will own the product layer between QXO's lakehouse and the applications that run the business. You will deliver the tooling that makes every data product easy to find, defined once, checked for quality and freshness, and fast and affordable to serve, working with data engineering, data governance, analytics, applied science and platform engineering teams.

Your work will turn a growing set of data products into a trusted foundation for analytics, AI agents, pricing, forecasting and future acquisitions. You will set the standards and build the tools teams use every day, and you will measure success by adoption and trust, not by launches.

Key Responsibilities

• Define the Data Product Tooling Vision: Develop and communicate the vision, strategy and roadmap for the tooling between the lakehouse and product applications.
• Own One Definition per Metric: Lead golden definitions for core entities such as customer, item, branch and sales, and the review and sign-off workflow that keeps every metric defined once.
• Set the Definition of Done for Data Products: Define production ready, including ownership, documentation, contracts, freshness and quality checks, with status visible from the platform.
• Build the Data Catalog and Access Experience: Deliver one place to find, register and request access to data products and metrics, with owner, definition, lineage, freshness and quality for each.
• Drive Serving, Cost and Performance Standards: Partner with engineering on materialization, partitioning and aggregates, plus cost labels and budgets, so analytics and AI workloads stay fast and affordable.
• Make Acquisitions Fast to Integrate: Own the onboarding kit that maps each acquired company's customer, product, pricing and sales data to common definitions.
• Grow Stewardship and Governance: Work with data governance and business owners to name data stewards and keep metadata, definitions and ownership current.
• Data-driven Decision Making: Define success metrics such as certified coverage, conflicting definitions retired, catalog usage and cost per query, and use them to drive the roadmap.

Qualifications & Skills

• 6+ years of Technical Product Management experience, with 3+ years on data platforms, data products or analytics infrastructure.
• 3 years of experience taking technical products from 0:1 end to end.
• Proven track record of launching data platform capabilities such as data catalogs, metadata management, semantic or metrics layers, data quality or data observability tools.
• Working knowledge of modern data stacks such as BigQuery, Snowflake or Databricks, dbt and orchestration tools.
• Ability to write SQL and read data models to validate definitions and requirements yourself.
• Experience setting standards across multiple engineering teams and driving adoption without direct authority.
• Strong planning, prioritization, and cross-functional communication skills.
• Bachelor's degree in Computer Science, Engineering, or related technical field, or equivalent practical experience.

Preferred Qualifications

• MBA or an advanced technical degree.
• Experience with data mesh or data as a product operating models, data contracts and federated governance.
• Experience with catalog and governance tools such as OpenMetadata, DataHub, Collibra, Atlan or Dataplex.
• Experience with master data management or entity resolution.
• Experience integrating data from acquisitions, ERP migrations or many source systems into a common model.
• Background in distribution, supply chain, manufacturing or other B2B industries with complex product and customer data.