Staff Analytics Platform Engineer

Join Our Future Health as a Staff Analytics Platform Engineer. In this role, you will shape the architecture, reliability, and future direction of the analytics platform. You will provide technical leadership across the entire analytics platform, define patterns and standards, and co-own the analytics platform architecture. You will also lead high-impact platform initiatives, own and evolve core platform components, and drive Snowflake performance and cost optimization. Additionally, you will collaborate with data product and engineering teams, influence how teams design and interact with data systems, and provide technical mentorship to analytics engineers and platform engineers.

• Co-owning the analytics platform architecture, designing end-to-end solutions across Snowflake, ingestion pipelines, dbt infrastructure, semantic layers, and secure analytics environments.
• Defining and driving the long-term technical vision for the analytics platform, ensuring it is scalable, cost-efficient, secure, and easy for data consumers to use.
• Leading high-impact platform initiatives that improve performance, developer experience, cost efficiency, or operational maturity.
• Experience supporting secure notebook environments (Coder, Jupyter, RStudio)
• Clear, influential communication skills with the ability to align teams around platform strategy
• Experience with Kubernetes and cloud‑native environments
• Expertise in analytics data modelling and how modelling choices affect performance, cost, and usability
• Familiarity with semantic layers and BI tooling (e.g. Omni)
• Deep experience building and running modern data platforms in complex, multi‑team environments
• Knowledge of Terraform, data governance models, and data observability tooling
• Experience mentoring engineers and raising capability across data and platform teams
• Proven technical leadership across infrastructure, ingestion, transformation, and analytics enablement
• Ability to diagnose complex, cross‑cutting issues across data, infrastructure, and analytical workloads
• Hands‑on experience with ingestion/orchestration tooling (e.g. Airbyte) and scaling pipelines across many sources
• Excellent Python engineering skills and the ability to design scalable, reliable platform components
• Hands‑on dbt and analytics CI/CD experience
• A track record of improving developer experience and reducing friction in data development
• Comfort working in regulated environments with strong governance and audit needs
• Strong platform architecture experience: Snowflake, dbt execution, semantic layers, secure analytics environments