Analytics Program Lead

About the role:

We're looking for a Senior / Staff Analytics Program Lead to own the analytics product program across our global Analytics organization. While our solution analytics leads own the definitions and insights for a single solution, this role owns the analytics product function as a system: how analytics products get built, how they hold together across solutions, and how fast we can ship the next one. You are accountable for the coherence, quality, and velocity of everything the analytics function delivers, internal and external, and for steering the function toward more self-serve and agentic analytics, where trusted metric definitions let customers, internal teams, and AI agents answer more questions without an analyst in the loop.

This is a hybrid role. Most of your time goes to running the program: enforcing and evolving the analytics standards and ways of working that let each pod ship correctly, scoping and sequencing work across solutions, and partnering with platform, data/BI engineering, and context architecture to shape the technical & semantic foundations our analytics products are built on, especially as we scale towards enabling increased self-service with AI tools. The rest is hands-on. You will jump into a domain as an individual contributor when the hardest problems need you, both to unblock the team and to stay closely aligned the work you're setting the bar for. If you are energized by taking a pattern you know works and re-establishing it at a broader scale, this is that role.

Key Responsibilities:

At Qventus, Analytics is treated as a first-class product, rather than a secondary output. As the Analytics Program Lead, you will:

• Own delivery of coherent, high-quality, on-time analytics products across solutions, and hold the bar for products that are stable, maintainable, and easy to iterate and enhance over time
• Increase the velocity at which we build and ship analytics products by enforcing and shaping standards, developing analytics AI skills and context, and evolving team structures, in partnership with our Data Engineering, BI Engineering, and Product teams
• Lead the solution analytics leads as their manager, owning how the analytics team works day to day, scoping and sequencing work across solutions, and keeping people unblocked and focused
• Partner with our Data Platform Manager and Data Context & Semantic Architect to shape the BI platform and semantic architecture that supports both our standard embedded analytics products and the move toward self-service analytics (incl. Analytics agents)
• Stay hands-on, contributing directly as an IC in a domain when the work demands it, to unblock the team and to keep close to the craft you're holding others to

What We're Looking For:

• Demonstrated program ownership of a technical function: you have scoped, sequenced, and shipped analytics or data work across multiple parallel workstreams and held ultimate responsibility for quality and coherence, not just your own output
• Strong analytical rigor: you can take an ambiguous question to a precise, defensible answer, with the hands-on depth (SQL/dbt, modern warehouse and BI) to do the work yourself and set the standard, not just review against it
• A systems-builder instinct: you turn what works into repeatable process, standards, and enforcement that keep running without you, rather than holding the function together through personal effort
• Cross-functional influence across teams you don't directly control, with a track record of driving alignment when interpretations differ and holding durable working relationships with platform, engineering, and architecture partners
• Comfort with ambiguity and scale: you can take a coherent way of working that you've proven and re-establish it at broader scale across solutions and teams

It's a Plus if You Have…

• Expertise in the healthcare domain and familiarity with healthcare operational data, clinical workflows, hospital operations, or common healthcare measurement challenges
• Experience scaling an analytics function at a growing company, taking something that worked at smaller scale and rebuilding it as a system others can run
• Familiarity with data governance, metric governance, or semantic layer concepts, especially where consistency across teams, solutions, or customer implementations is critical
• Experience with data logic implemented in dbt and data visualization in Sigma, and with knowledge management systems for documenting metric definitions and analytical decisions
• Exposure to AI-enabled analytics, natural language analytics, or agentic analytics workflows, especially where high-quality metric definitions and trusted analytical context are required for safe and useful AI outputs