Senior Product Manager - Data Platform and Analytics

The Senior Product Manager is a skilled product practitioner with demonstrated ability to drive significant business impact while developing sophisticated strategic capabilities. They operate with high autonomy in complex business domains while maintaining appropriate engagement with leadership on strategic direction. They identify and execute on high-value opportunities, build effective cross-functional partnerships, and deliver measurable outcomes that advance Pie's strategic goals.

You will report to the Director of Product for Data and Post-Bind Journeys (financial systems, premium audit, and claims) and work closely with Data Engineering leadership, Data Science teams, and cross-functional partners to identify opportunities, prioritize initiatives, and drive end-to-end execution from conception to impact measurement. You'll manage backlogs across analytics and platform domains, diving into detail mode from an understanding perspective.

Mission For This Role

The Senior Product Manager for Data Platform & Analytics will drive critical initiatives that enhance Pie's data infrastructure and analytics capabilities, focusing on improving data quality and platform capabilities, accelerating analytics delivery, and expanding data self-service capabilities across the organization. This role will contribute to making data and analytics a competitive advantage for Pie through reliable infrastructure and accessible insights.

Data Platform:

The Data Platform team builds the infrastructure that moves data from operational systems to our analytical environment This role requires deep technical understanding to make informed product decisions while working closely with Data Engineering teams who own technical implementation.. You'll provide product oversight and prioritization for ETL pipeline improvements using tools like Snowflake and Airflow, prioritizing reliability, observability, and efficiency. You'll manage the transition from legacy data sources to system-generated data, reducing manual intervention and increasing automation.Your technical fluency will enable you to make informed product decisions while partnering with engineering teams who own implementation and defining product requirements that enable scalable analytics. 

Analytics Enablement:

You'll focus on creating and prioritizing  self-service analytics capabilities that empower teams across Pie to make data-driven decisions independently. This includes developing data marts, improving data discoverability, and building tools that enable business users to access and analyze data efficiently. You'll work closely with business stakeholders to understand their analytical needs and translate them into scalable data products that reduce dependency on manual reporting and ad-hoc analysis.

Key Outcomes For First 12 Months:

• Strategic Roadmap Development: Develop a comprehensive data platform and analytics roadmap for your domain that balances technical excellence with tangible business impact, clearly connecting improved data capabilities to Pie's competitive advantage in the mid/high risk workers comp and commercial auto segments.
• Product Operating Model Integration: Successfully integrate your data platform domain within Pie's Product Operating Model, adapting ceremonies and workflows to accommodate the unique characteristics of data products while maintaining agile principles.
• Cross-functional Partnership Building: Build strong, collaborative relationships with technology and business leaders across Pie, establishing yourself as a trusted product partner on data platform strategy and analytics implementation through both technical expertise and business acumen.
• Data Reliability Improvement: Partner with engineering to identify and prioritize improvements that will allow for more durable data contracts between operational systems and data pipelines.
• Manual Process Reduction: Develop and execute a strategy for progressively reducing reliance on manual/spreadsheet-based data sources and reporting, with clear priorities based on business impact and technical feasibility.
• Measurement Framework Implementation: Create and implement a measurement framework for data quality, pipeline reliability, and analytics performance that enables data-driven decision making across your domain.
• Self-Service Analytics Enhancement: Enhance data infrastructure to enable self-service analytics capabilities, focusing on data marts and tools that reduce dependency on manual reporting and empower business users to access insights independently.
• Governance Collaboration: Collaborate on data governance strategy including working with compliance and security teams to ensure data meets regulatory and industry standards while enabling efficient analytics access.

• 8+ years overall professional experience working on complex business and/or technology problems.
• 6+ years Product Management experience working in an agile software development lifecycle (SDLC) environment.
• Advanced SQL proficiency and data fluency are required, with hands-on experience writing queries for analysis and data validation.
• Demonstrated experience working with data platforms, analytics, or business intelligence products — ideally across both infrastructure and applied analytics domains.
• Familiarity with modern data stack tools such as Snowflake, Airflow, dbt, Fivetran, Monte Carlo, Looker, or Tableau.
• Strong understanding of the data lifecycle to include data modeling, data quality, analytics enablement, and self-service capabilities — with a track record of driving adoption and alignment across teams in the context of product management.
• Ability to translate complex technical work into clear business impact, supporting your recommendations with data and strategic rationale.
• Strong communication skills with the ability to influence stakeholders and align cross-functional priorities while maintaining appropriate engagement with leadership on strategic direction.
• Growth mindset and resilience — you seek feedback, own outcomes, and collaborate effectively through ambiguity with curiosity and accountability.
• Experience managing complex product deliveries end-to-end with ability to coordinate across engineering and design functions.
• Track record of implementing measurement approaches to track business outcomes and iterating toward target impacts.
• Sound judgment about when to operate in detail mode vs. remaining at a higher level of abstraction, with ability to take ownership while effectively managing scope evolution.

The use of AI in Application Review: To support a fair, efficient, and consistent hiring process, we use AI-powered tools to assist in the initial screening of applications. These tools help us identify qualifications and prior work experiences that align with the requirements of the role. All AI-reviewed applications are still subject to human oversight and decision-making at multiple stages of the process. By submitting your application, you acknowledge and consent to Pie utilizing these AI technologies to assist in our evaluation process.