Senior Analytics Platform Engineer

Our success in rapid scale across the globe is backed by some of the world's leading investors. At Qventus, you will have the opportunity to work with an exceptional, mission-driven team across the globe, and the ability to directly impact the lives of patients. We’re inspired to work with healthcare leaders on our founding vision and unlock world-class medicine through world-class operations.

About the role:

We’re looking for a Senior Analytics Platform Engineer to join our global Analytics organization. This US-based, remote role sits at the intersection of analytics, platform engineering, and tooling expertise. You will play a critical part in enabling high-quality, scalable analytics across multiple Qventus solutions by owning and advancing our enterprise analytics platform - most notably Sigma, our primary visualization tool.

In this role, you will combine your technical expertise, product mindset, and platform-oriented thinking to ensure that our analytics infrastructure is reliable, intuitive, and ready to support the needs of both internal teams and healthcare system customers. You’ll partner closely with product analytics, analytics engineering, data architecture, and solution teams to optimize Sigma usage, improve analytics performance, support cross-solution deployments, and inform the evaluation of emerging AI-enabled analytics and self-service tools.

This role is ideal for someone who thrives in ambiguity, enjoys shaping foundational tools and processes, and is energized by improving the speed, stability, and usability of analytics at scale.

Key Responsibilities:

At Qventus, Analytics is treated as a first-class product, rather than a secondary consideration. As a Senior Analytics Platform Engineer, you will:

• Serve as a primary platform owner for Sigma, ensuring reliability, performance ,secure configuration, and smooth day-to-day operation across multiple Qventus solutions.
• Interact regularly with BI vendors, including Sigma, to understand their feature roadmap and how it will impact our ability to provide next-generation analytics to our customers
• Develop and maintain reusable Sigma assets, including templates, components, data models, and governance patterns, that allow analytics teams to build consistently and efficiently.
• Partner with data engineering teams to ensure dbt pipelines and data models are optimized for downstream analytics consumption
• Create and implement standards for dashboard performance and integrity across the analytics platform
• Contribute to cross-solution deployment strategies to ensure analytics scale reliably and consistently
• Participate in the evaluation and support of AI-assisted analytics tooling, semantic layer technologies, and emerging self-service analytics platforms
• Prototype, test, and document new analytics features or AI-driven enhancements that could improve user experience, accelerate insights, or reduce manual effort
• Provide technical thought leadership on long-term platform evolution, architectural choices, and cross-tool integration
• Provide team leadership in ways that inspire and can help guide others on the team

What We’re Looking For: 

• 8+ years experience as an engineer in a data role (data engineering, data platform, machine learning engineering, analytics engineering etc.) incl. familiarity with data modeling techniques (including dimensional and semantic) and tools (e.g., DBT, Databricks Unity Catalogue) and modern Data Warehouses (eg. Snowflake, Databricks)
• Experience optimizing datasets for BI tools, ideally in a dbt-centric environment
• Deep expertise in at least one modern BI tool - Sigma preferred
• Strong technical and product intuition, with an inclination toward scalable, maintainable solutions
• Comfort navigating complex, interrelated datasets and platform configurations
• Passion for operational excellence, documentation, and enabling others
• 3+ years of experience supporting platform BI tooling (Sigma preferred, but also Power BI, Tableau, Looker, etc)

• Exceptional communication and organizational skills, with a proven ability to lead conversations, coordinate cross-functional teams, and drive projects to completion by aligning stakeholders, managing timelines, and ensuring clear and actionable documentation of complex data assets and requirements.

It’s a Plus if You Have… 

• Expertise in the healthcare domain and familiarity with domain data-specific challenges such as codes/terminology (e.g. CPT, ICD), compliance (HIPAA), and interoperability standards (e.g., HL7, FHIR).
• Experience working with data governance frameworks or tools to ensure compliance and consistency across data assets.
• Proficiency with knowledge management systems (e.g., Notion) to organize documentation and foster team-wide transparency.
• Prior experience evaluating or implementing AI-enabled analytics tools or LLM-powered self-service workflows
• Strong understanding of Git and version control practices
• Educational background in analytics, computer science, engineering, statistics, or a related field