Senior Product Manager Data (Remote)

Role: Sr. Product Manager, Data

Base Pay Midpoint: $150,038

Location: Denver / Remote

Who Is Covered?

At Covered, we are focused on making insurance easy to understand and painless to purchase. We combine intuitive technology with a human touch to help consumers quote, compare, and purchase multiple insurance products in minutes. By partnering with lenders, financial institutions, and fintech companies, we deliver our personalized embedded insurance marketplace to their customers.

What Is Covered?

The best-in-class B2B2C embedded insurance marketplace built specifically for fintechs. We combine award-winning digital insurance experiences, innovative technology, and industry-leading compliance programs to help our partners build a fully digital insurance experience using our APIs, pre-built UI components, and full-service licensed stack.

About This Role

We are seeking a highly skilled and motivated data leader to partner with our team of analysts and drive data-driven decision-making across the business. In this role, you will be responsible for ensuring that our data processes are robust, scalable, and aligned with our business goals. You’ll play a pivotal role in turning data into actionable insights that will shape our strategy and operations in a fast-paced startup environment.

Yep, We Have Benefits!

At Covered, our cultural DNA is our brand! This position includes a competitive benefits package to include an extraordinary culture, medical, dental, vision, FSA, HSA, AD&D, Life Insurance, STD, LTD, 401(k), casual time off, and 11 paid holidays.

Key Responsibilities:

• Own the Data Product Roadmap:

  • Define and deliver the vision, strategy, and execution for Covered?s data initiatives, including the management of the data lake in partnership with data engineering to support product analytics, partner analytics, and internal business intelligence.

  • Prioritize and manage the product analytics platform to provide real-time insights that empower better decision-making for product and business teams.

  • Drive partner analytics, ensuring our external stakeholders have the insights they need to maximize the value from their partnerships with Covered.

  • Lead the development of internal BI tools to enable data-driven decision-making across sales, marketing, and agency operations teams.

• Data Lake Management & Strategy:

  • Oversee the architecture, scalability, and performance of the data lake, ensuring it meets the growing data needs of Covered.

  • Ensure data is properly ingested, processed, and accessible for analysis and reporting by teams across the organization.

  • Manage Databricks integration or similar platforms, leveraging them to optimize workflows, streamline data pipelines, and support advanced analytics.

• Leadership & Cross-Functional Collaboration:

  • Ensure data accuracy and governance through cross functional enablement work with teams creating or modifying data sources.

  • Manage and lead a team of data engineers and analysts, fostering a collaborative and high-performing culture.

  • Work cross-functionally with product managers, business development, sales, marketing, and leadership to define data needs, make work visible, and ensure alignment with organizational goals.

  • Act as a key liaison with the engineering team to ensure smooth integration and delivery of data products.

• Strategic Data Management:

  • Develop scalable data strategies, ensuring our platforms and tools meet the growing needs of the company and partners.

  • Enable transparency in data operations, building processes that clarify the availability, usage, and reliability of insights across all teams.

  • Define KPIs for product and partner analytics, ensuring that data-driven insights support key strategic initiatives.

• BI Enablement:

  • Lead the charge in building out internal BI tools for our sales, marketing, and insurance agency performance teams.

  • Ensure that the data tools and dashboards you deliver are user-friendly, intuitive, and directly support actionable insights.

  • Make work visible across the company by building dashboards, running training sessions, and embedding data into everyday operations.

Role Accountabilities Include, But Are Not Limited To:

• Team Leadership & Development:

  • Partner with, lead, and mentor a team of data analysts, providing guidance on best practices, tools, and techniques.

  • Foster a collaborative and inclusive team culture that promotes continuous learning and professional growth.

  • Set clear goals and performance metrics for the team, ensuring alignment with business objectives.

• Data Management & Analysis:

  • Oversee the collection, organization, and analysis of data to support business decision-making.

  • Conduct hands-on data analysis to identify trends, insights, and opportunities for business improvement and superior outcomes.

  • Develop and maintain dashboards, reports, and other data products that provide actionable insights to stakeholders.

• Tooling & Automation:

  • Design and build data tools and automated processes to enhance data accessibility and usability across the organization.

  • Collaborate with stakeholders to understand business needs and translate them into technical requirements.

  • Ensure the scalability, reliability, and efficiency of all data tools and systems.

• Data Engineering Partnership:

  • Partner with the engineering team on data engineering projects, including the development of data pipelines, integration of data sources, and data warehousing solutions.

  • Contribute to the design and implementation of data architecture that supports both current and future business needs.

  • Ensure data integrity, security, and compliance with industry standards and regulations.

• Cross-Functional Collaboration:

  • Work closely with product, marketing, finance, and other teams to support data-driven decision-making.

  • Serve as a key point of contact for data-related inquiries and initiatives across the organization.

  • Provide training and support to non-technical stakeholders on data tools and best practices.