Analytics Engineering Manager

SmarterDx is a clinical AI company focused on optimizing healthcare revenue through innovative data solutions. They are seeking an experienced Analytics Engineering Manager to lead their Core Analytics Team in building a new analytics data platform, overseeing analytics architecture, and ensuring effective team collaboration and growth.

Responsibilities:

• Design, implement, and migrate to a new analytics warehouse, owning modeling patterns, layer contracts (Silver, Gold, Semantic), and metric definitions
• Define interfaces and responsibilities across ingestion, transformation, and analytics to improve velocity and trust
• Identify how the Data Analysts and Analytics Engineers work together on the team’s goals
• Launch Omni for client-facing analytics, establish best practices, and train Product and Business Analysts
• Specify and integrate tools for data quality, anomaly detection, and monitoring
• Scale the Core Analytics team from 4 to 8
• Support analytics infrastructure for 10 products (9 net new)
• 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
• 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
• 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

Requirements:

• 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
• Technical skills: SQL (Advanced)
• Technical skills: dbt (Advanced)
• Technical skills: BI/data visualization tools (Proficient)
• Technical skills: Python for data (Proficient)
• Technical skills: Git (Proficient)
• 2+ years working with healthcare data (clinical, billing, or both)