Senior Product Manager: Data and Implementation Tools

Location: Remote (EST/CST preferred), NYC area encouraged

About the Role

We’re seeking a strategic yet hands-on Senior Product Manager to own the development of Rightway’s data and implementation tools—critical products that power our healthcare data ecosystem, streamline customer onboarding, and unlock actionable insights for clients and internal teams.

In this role, you will lead a small, dedicated team (Data Operations Manager and Project Manager) and partner closely with engineering, analytics, security, and client-facing stakeholders. You will set the vision, roadmap, and delivery plan for both internal and external-facing data products, ensuring they are scalable, reliable, and built to deliver measurable value. This is a mission-critical position at the intersection of healthcare data, process optimization, and client delivery.

About Rightway

Rightway is on a mission to harmonize healthcare for everyone, everywhere. Our products guide patients to the best care and medications by inserting clinicians and pharmacists into their care journey through a modern, mobile app.

Since 2017, we’ve raised over $130M from leading investors including Khosla Ventures, Thrive Capital, and Tiger Global, at a $1B valuation. We’re headquartered in New York City, with satellite offices in Miami and Denver, and a distributed remote workforce. Our clients rely on us to transform the healthcare experience, improve outcomes, and reduce costs.

What You’ll Do

Product Strategy & Vision

• Own the roadmap for Rightway’s data and implementation products, balancing strategic investments with quick wins.
  
  
• Identify and prioritize high-impact opportunities in collaboration with internal business stakeholders, clients, and technical teams.
  
  
• Define clear product outcomes and success metrics that align with company goals and client needs.
  
  

Execution & Delivery

• Translate business requirements into detailed user stories, acceptance criteria, and data mapping specifications.
  
  
• Manage a well-prioritized backlog, ensuring alignment across engineering, analytics, and operational teams.
  
  
• Lead agile ceremonies and ensure smooth execution of releases and iterations.
  
  
• Deliver “thin-slice” solutions to provide early value and iterate based on feedback.
  
  

Cross-Functional Collaboration

• Partner with data engineers, analysts, and IT/security to design secure, scalable data pipelines and integration workflows.
  
  
• Collaborate with implementation teams to build tools that reduce onboarding time, improve data quality, and increase automation.
  
  
• Lead process improvement initiatives to eliminate operational bottlenecks.
  
  

Who You Are

Required Experience

• 5+ years working on data products in any capacity.
  
  
• 3+ years as a product manager with a track record of delivering data-focused products or internal tools.
  
  
• Ability to identify when process improvements or technology investments are the right lever to achieve business goals—and see them through to completion.
  
  
• Experience in healthcare strongly preferred; PBM or medical claims processing experience highly preferred.
  
  
• Passion for and experience in startup or high-growth environments.
  
  

Preferred Experience

• Familiarity with AWS services such as S3, Lambda, dbt, SageMaker, and ETL processes.
  
  
• Basic knowledge of Python, PySpark, or other data transformation tools.
  
  
• Exposure to AI/ML applications in data products (e.g., predictive modeling, claims categorization).
  
  

Traits That Set You Apart

• A systems thinker who can simplify complex data workflows for any audience—from executives to engineers.
  
  
• A creative problem-solver who defines the problem before pursuing solutions.
  
  
• A “data nerd” who thrives on untangling complex datasets to drive meaningful outcomes.
  
  
• An empathetic communicator who builds trust across technical and non-technical teams.
  
  

What Success Looks Like

• Reduced time-to-value for new client onboarding.
  
  
• Measurable improvements in data quality and pipeline reliability.
  
  
• Increased automation and reduced manual intervention in key processes.
  
  
• High adoption of internal implementation tools by cross-functional teams.