Analytics Engineering Manager
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Requirements
• What You • 3-5+ years of experience managing senior data professionals • Prior hands-on experience as a Data Analyst, Analytics Engineer, or Data Engineer • Strong track record leading cross-functional data initiatives • Experience in startups or scaling mid-sized businesses • BI/data visualization tools (Proficient) • Python for data (Proficient) • Git (Proficient) • 2+ years working with healthcare data (clinical, billing, or both) • Our Tech Stack • ELT: dbt cloud and core • Semantic Layer: dbt MetricFlow • BI: Hex (internal exploration) and Omni (embedded, production-grade analytics) • Orchestration: Airflow
Responsibilities
• Core Team priorities for 2026: • Analytics data warehouse v2: Design, implement, and migrate to a new analytics warehouse, owning modeling patterns, layer contracts (Silver, Gold, Semantic), and metric definitions. • Analytics data warehouse v2: • Clear layer ownership: Define interfaces and responsibilities across ingestion, transformation, and analytics to improve velocity and trust. • Clear layer ownership: • Clear role definitions: Within the Core team, identify how the Data Analysts and Analytics Engineers work together on the team’s goals. • Clear role definitions: • Embedded analytics: Launch Omni for client-facing analytics, establish best practices, and train Product and Business Analysts. • Embedded analytics: • Production analytics tooling: Specify and integrate tools for data quality, anomaly detection, and monitoring. • Production analytics tooling: • Team growth: Scale the Core Analytics team from 4 to 8. • Team growth: • Platform scale: Support analytics infrastructure for 10 products (9 net new). • Platform scale: • How You’ll Spend Your Time • 40% Project & Stakeholder Leadership • Translate business and product needs into durable analytics designs. • Lead high-impact analytics initiatives tied to achieving OKRs and company strategic expectations. • Standardize tools and processes to improve scalability and consistency. • Help stakeholders navigate tradeoffs across correctness, latency, flexibility, and cost. • 30% Analytics Strategy & Execution • Own analytics engineering standards, modeling philosophy (3NF EDW, dimensional marts), and semantic layer design. • Build data models and semantic layer objects that are appropriately balanced for exploratory flexibility with production-grade rigor. • Ensure metrics are consistent, discoverable, and trusted across internal and client-facing use cases. • Establish testing, validation, data quality, and governance practices. • 30% Team Leadership • 30% Team Leadership • Build a culture of ownership, curiosity, and technical excellence. • Mentor and develop all members of the Core team: both senior Data Analysts and Analytics Engineers. • Run structured performance and growth reviews. • Identify and address skills gaps and resourcing needs.
Benefits
• Medical, Dental & Vision – Comprehensive plans with leading insurance providers, covering 75% of your premiums, depending on the plan. • Medical, Dental & Vision • Paid Parental Leave – Generous paid leave to support families through birth or adoption: Up to 12 weeks for parents. • Paid Parental Leave • Remote-First Team – Work from anywhere in the U.S. • Remote-First Team • Unlimited PTO & 10 Holidays – So you can relax and recharge. • Unlimited PTO & 10 Holidays • 401(k) with Traditional & Roth Options – Tax-advantaged retirement savings through Fidelity with a 4% match. • 401(k) with Traditional & Roth Options • Minimal Bureaucracy – A fast-moving, high-impact environment where you can focus on what matters. • Minimal Bureaucracy • Incredible Teammates! – Work alongside smart, supportive, and mission-driven colleagues. • Incredible Teammates!