Senior Analytics Engineer

Join Qventus as a Senior Analytics Engineer, where you'll lead an analytics pod and build trusted analytical products. You'll partner with product teams, define metrics, design visualizations, and ensure the rigor of the results. You'll also manage project scoping, sprints, and ticketing, while holding ultimate accountability for the quality of the deliverables. This role offers a chance to tell stories with data, lead small teams, and contribute to the organization's analytics standards.

• Lead the analytics pod in day-to-day operations, ensuring the quality of deliverables and managing project scoping and planning.
• Partner with product managers to turn product ideas into technically defensible analytics products, defining metrics and shaping the dashboard narrative.
• Build and steward metric definitions and semantic context for the pod's scope, ensuring analytical rigor and correctness.

• Versatile critical thinking, with demonstrated ability to ramp up quickly and translate general skills into tactical enablement, even without deep domain expertise
• Sharp, experienced analytical thinking, with a track record of building out high-quality, narratively complete analytical components, not just running ad hoc analyses
• Strong data visualization design & BI development skills (Sigma or similar)
• Demonstrated ability to partner with PMs as a trusted peer, turning rough ideas into defensible products and pushing on the thinking without friction
• Hands-on expertise with SQL and modern data warehouses (DBX preferred): deep enough to run analysis, support and debug metric definitions, and set the technical standard for your pod
• Experience leading delivery for a small team: comfortable owning sprints, sequencing, and coordination, and getting good work out of a pod without becoming the bottleneck
• Experience leading dashboard development end to end, from design through validation and including hands-on build
• Expertise in the healthcare domain and familiarity with healthcare operational data, clinical workflows, hospital operations, or common healthcare measurement challenges
• Familiarity with data governance, metric governance, or semantic layer concepts, especially where consistency across teams, solutions, or customer implementations is critical
• Deeper technical expertise with hands-on data modeling and transformation experience and standards setting (dbt preferred)
• Experience contributing to analytics QA processes, validation workflows, peer review practices, or release readiness checks for customer-facing analytics