Sr. Technical Product Manager

Guidepoint is seeking a Senior Technical Product Manager to lead the strategy, roadmap, and evolution of the company's data ecosystem.

This role will own the vision and prioritization for Guidepoint'sexternal and internal data assets, ensuring the organization has the data capabilities necessary to support growth, product innovation, operational efficiency, and AI-driven initiatives. Technical Product Manager will act as the primary business owner for Guidepoint's data platform, partnering closely with Engineering, Compliance, Commercial Operations, Product, and Executive Leadership. The role will oversee external data vendor relationships, identify gaps in Guidepoint's data capabilities, define requirements for new data products and integrations, and drive improvements in data quality and utilization.

The position will directly manage the Data Analyst function and work closely with Engineering teams responsible for ingestion, processing, and data infrastructure.

Hybrid role in our Toronto office.

• Ownthe roadmap for Guidepoint'sdata platform and data capabilities.
• Identify strategic gaps in Guidepoint'sdata ecosystem and recommend investment priorities.
• Evaluate opportunities to expand or enhance
  
  Guidepoint'sdata assets through external partnerships andnew technologies.
• Develop business cases and success metrics for data initiatives.
• Present recommendations and roadmap priorities to executive leadership.

• Own relationships with external data providers and strategic data partners.
• Evaluate new data sources for quality, coverage, scalability, and business value.
• Assess prospective data providers for their ability to improve entity coverage, enrichment capabilities, and overall data quality.
• Define requirements and success criteria for vendor onboarding initiatives.
• Partner with Legal and Compliance on contract reviews and vendor governance.
• Monitor vendor performance and drive ongoing optimization of Guidepoint'sdata portfolio.

• Translate business needs into product requirements for data ingestion, enrichment, normalization, and quality initiatives.
• Own requirements and prioritization for entity matching,identity resolution, deduplication, and data enrichment capabilities.
• Partner with Data Engineering teams to improve matching accuracy,enrichment workflows, and master record management processes.
• Prioritize engineering investments across competing data initiatives.
• Partner with Engineering to deliver scalable data capabilities.
• Define acceptance criteria and success metrics for new datasets and integrations.
• Drive adoption andutilizationof new data capabilities across the organization.

• Establish frameworks for measuring and improving data quality.
• Define andmonitormetrics for data completeness, accuracy, consistency, freshness, duplication, and match quality.
• Def inequality KPIs and operational scorecards.
• Prioritize remediation efforts and quality improvement initiatives.
• Drive initiatives to improve entity resolution accuracy, reduce duplicate records, and increase trust in Guidepoint'sscore data assets.
• Partner with Engineering and business stakeholders to addressrootcauses of quality issues.

• Manage the Data Analyst function.
• Oversee analysis of existing and prospective data assets.
• Develop reporting on data quality, coverage,utilization, and ROI.
• Monitor and report on match rates, enrichment effectiveness, data quality trends, and external data source performance.
• Support strategic decision-making through data-driven insights and recommendations.

• Serve as the primary point of coordination between Product, Engineering, Compliance, Commercial Operations, and Executive Leadership on data initiatives.
• Align stakeholders around priorities, tradeoffs, and investment decisions.
• Communicate roadmap progress, risks, and opportunities.

• 7+ years of experience in Product Management, Data Product Management, Technical Product Management, or related roles.
• Experience owning data products, data platforms, or data-intensive systems.
• Experience working with modern data platforms such as Databricks, Snowflake,Big Query, Redshift, or similar cloud-based data ecosystems.
• Strong understanding of data acquisition, data quality, data governance, and data lifecycle management.
• Experience with entity resolution, record matching, deduplication, data enrichment, or Master Data Management (MDM) initiatives.
• Experience working with external data vendors and third-party datasets.
• Strong analytical capabilities, including SQL, data analysis, and experience using analytics and business intelligence tools to evaluate data quality, coverage,utilization, and business impact.
• Demonstrated ability to influence technical and business stakeholders.
• Experience partnering closely with engineering teams to deliver complex technical initiatives.
• Experience partnering with Data Engineering teams on data ingestion, transformation,…