Staff Analytics Engineer

About the role

Join Rula as a Staff Analytics Engineer, where you will lead the migration to Snowflake and Medallion architectures, act as a bridge between engineering and business strategy, optimize warehouse performance, enforce CI/CD testing gates, and drive the adoption of AI-assisted tools. Enjoy remote work, generous benefits, and the opportunity to make a significant impact on the company's data ecosystem. Key missions: Lead the design and execution of Rula’s migration to Snowflake, establishing structural blueprints and execution playbooks.. Act as a critical technical bridge between engineering and business strategy, negotiating technical boundaries with leadership.. Own Snowflake compute-cost profiling and warehouse performance globally, establishing and governing financial and operational baselines. Profile: - 6+ years of professional experience in analytics engineering, data architecture, or data engineering, with a proven track record of operating at a systems-level to drive organization-wide data strategies, cross-domain workflows, or platform architecture - Proven experience acting as a bridge between technical execution and business strategy, with strong judgment to surface risks, discuss trade-offs, and negotiate intake guardrails with leadership - Expert-level SQL proficiency and production experience designing data models using Medallion architectures - 2+ years of hands-on experience utilizing dbt to build, orchestrate, and test production-grade ELT pipelines - Deep expertise in production git workflows with a proven ability to design, build, and enforce automated CI/CD testing gates - Experience leading the architectural design, optimization, or migration of a modern cloud data platform (Snowflake, Redshift, BigQuery) supporting multiple cross-functional business domains - Demonstrated track record of driving technical leverage by scaling the adoption of AI-assisted tools across a team (e.g., productizing prompt banks or integrating AI code reviews) - Experience building infrastructure that integrates with headless BI semantic layers (e.g., Cube.dev) and downstream AI agentic workflows (e.g., LibreChat) - Prior experience working with HIPAA-compliant data environments, electronic health records (EHR), or digital health operations - Basic Python proficiency for pipeline and tool orchestration - Experience managing changing business processes or schema drift to gracefully adapt data models - Advanced knowledge of implementing robust RBAC frameworks, hashing, and masking strategies for sensitive clinical data