Job Description In this role, the VP of Product – Data Systems will take ownership of the company’s full data practice and drive the evolution of its data ecosystem. They will oversee how data powers both internal operations and customer-facing solutions, ensuring data enables targeted insights, relevance, and performance across the business. This includes enabling data for internal organizational needs, steering external data experiences such as a self-serve portal and emerging agentic tools for clients, and managing the data components that support every functional area. The VP will guide the packaging, design, and creation of the company’s data practice while leading large-scale engineering teams and collaborating deeply across departments to deliver enterprise-grade solutions. This role is onsite 4x a week in Denver, CO Compensation for this position is between $325,000 to $375,000 We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements Extensive big data experience within a large enterprise environment Strong understanding of internal and external data practices Engineering knowledge related to AI, data platforms, and large-scale data architecture Demonstrated leadership with forward-thinking, strategic, big-picture capabilities Experience overseeing engineering-heavy teams (20–30 engineers plus contractors) rather than purely product organizations Hands-on familiarity with Databricks and Snowflake migrations or operations Proficiency with AWS cloud environments Highly collaborative with a strong sense of ownership and ability to drive initiatives forward Background can be product or technical product, as long as it aligns with enterprise-level scale