Manager- Analytics Engineering

PANTHERx is the nation’s largest rare disease pharmacy, prioritizing the patient experience in all aspects of our work. We seek team members who are inspired, compassionate problem solvers producing high-quality work and thriving in the dynamic environment of modern medicine. Committed to superior health outcomes for people living with rare diseases, PANTHERx cultivates talent and encourages career growth within a mission-driven culture.

About the role

The Manager, Analytics Engineering leads the Analytics Engineering track within the Data & Analytics organization, owning the semantic layer between raw pipeline output and BI consumption. This role establishes governed, reusable metric views as the canonical source of truth for business metrics, enabling consistent analytics delivery across BI, external partner feeds, and AI model inputs.

Responsibilities

• Semantic Layer Ownership
  • Owns the Unity Catalog semantic layer as the governed source of truth for all business metrics, including metric view definitions, Silver-to-Gold promotion logic, data mart architecture, and data product development.
  • Ensures every business metric is defined once as a metric view and consistently available to downstream consumers such as Power BI dashboards, external partner feeds, internal analytics, and AI model inputs.
  • Sets and enforces standards for metric view design, naming conventions, versioning, and documentation, aligned with Data Governance and Unity Catalog access controls.
  • Partners with Data Architecture on Gold-layer design to ensure scalability and maintainability.
• Data Product Development
  • Leads development of reusable data products in Unity Catalog, enabling self-service analytics discovery.
  • Ensures analytics requests include defined acceptance criteria and data product specifications before build work begins.
  • Drives consistency by replacing bespoke SQL derivations with governed, versioned metric views and data products.
• Team Leadership & Development
  • Develops a team culture centered on the semantic layer discipline, distinct from Data Engineering and Analytics & BI.
  • Builds individual development plans and career frameworks for team growth within Analytics Engineering.
  • Fosters adherence to standards, documentation, and reusability in data product development.
• Cross-Functional Partnership
  • Partners with Analytics & BI to ensure metric views meet consumption requirements without re-deriving logic.
  • Collaborates with Data Engineering to align Gold-layer tables and Silver-to-Gold promotion logic with platform architecture.
  • Works with Data Governance to ensure metric views are governed assets with assigned ownership, tracked lineage, and enforced metadata standards.
  • Coordinates with Informatics to define scope and acceptance criteria for analytics requests.
  • Supports QA in validating analytics outputs against governance-defined quality dimensions.

Requirements

• 7+ years of progressive data engineering or analytics engineering experience, with at least 2 years in people management or team leadership.
• Deep, hands-on expertise with Databricks: Unity Catalog, metric views, Delta Lake, medallion architecture, and Silver-to-Gold promotion logic in production.
• Experience owning or building a semantic layer function, including metric definitions and data product development for reuse across consumers.
• Clear understanding of analytics engineering as distinct from data engineering and BI; ability to articulate and hire for this discipline.
• Proficiency in SQL and PySpark to set engineering standards, review code quality, and make architecture decisions.
• Proven ability to build and lead teams, establishing standards in a function without pre-existing organizational identity.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or related field, or equivalent experience.
• Preferred: Healthcare, specialty pharmacy, or regulated industry experience with clinical or operational data.
• Preferred: Experience with data product design, catalogs, and self-service analytics in a governed Databricks environment.
• Preferred: Familiarity with data governance frameworks and semantic layer asset design for metadata and lineage standards.
• Preferred: Experience with data catalog tooling (Atlan, Collibra, or equivalent) and designing governed metric views.
• Preferred: Exposure to AI/ML platform integration and its impact on semantic layer design.
• Preferred: Familiarity with pipeline observability platforms (Monte Carlo or equivalent) and semantic layer monitoring.

Work Environment

This hybrid role operates in both home office and professional office settings. Routine use of standard office equipment (computers, phones, MS Teams) is required. The position involves regular sitting, standing, walking, and use of hands for tasks such as typing and data analysis. Visual acuity is necessary for screen-based work. Reasonable accommodations may be made for individuals with disabilities.

Benefits

• Hybrid, remote, and flexible on-site work schedules.
• Comprehensive benefits package including medical, dental, vision, HSA, and FSA options.
• 401K with employer matching, employer-paid life insurance, and short/long-term disability coverage.
• Employee Assistance Program (EAP).
• Generous paid time off for full-time employees, limited PTO for part-time, and paid holidays.