Senior Analytics Engineer

Current job opportunities are posted here as they become available.

7,000 Diseases - 500 Treatments - 1 Rare Pharmacy

PANTHERx is the nation’s largest rare disease pharmacy, and we put the patient experience at the top of everything that we do.

If you are looking for a career in the healthcare field that embraces authentic dedication to patient care, you don’t need to look beyond PANTHERx. In every line of service, in every position and area of expertise, PANTHERx associates are driven to provide the highest quality outcomes for our patients.

We are seeking team members who:

Are inspired and compassionate problem solvers;

Produce high quality work;

Thrive in the excitement of the ever-challenging environment of modern medicine; and

Are committed to achieving superior health outcomes for people living with rare and devastating diseases.

At PANTHERx, we know our employees are the driving force in what we do. We cultivate talent and encourage growth within PANTHERx so that our associates can continue to explore their interests and expand their careers. Guided by our mission to provide uncompromising quality every day, we continue our strategic growth to further reach those affected by rare diseases.

Join the PANTHERx team, and define your own RxARE future in healthcare!

Location: Pittsburgh, PA (Hybrid)

Classification: Exempt

Status: Full-Time

Reports to: Manager, Analytics Engineering

The Senior Analytics Engineer designs and builds the governed semantic layer on PANTHERx’s Databricks platform:
Unity Catalog metric views, Gold-layer table design, Silver-to-Gold promotion logic, and reusable data products. This role is responsible for establishing every business metric as a single, canonical, versioned definition that serves every downstream consumer:
Power BI dashboards via Direct Lake, external partner feeds, internal analytics, and AI model inputs. The Senior Analytics Engineer serves as a senior practitioner within the Analytics Engineering track, replacing bespoke, one-off SQL derivation with governed, reusable assets, setting the technical bar for semantic layer design, and mentoring Analytics Engineers as the team scales.

• Designs and builds Unity Catalog metric views as the canonical, versioned definitions of business metrics, with ownership assigned, lineage tracked, and access controls enforced.
• Designs Gold-layer tables and Silver-to-Gold promotion logic in partnership with Data Engineering, ensuring the semantic layer is architecturally sound, performant, and maintainable as the platform grows.
• Migrates legacy consumption logic, including EDW views, legacy data products, and ad-hoc SQL derivation, into governed metric views with validated output parity.
• Sets and enforces standards for metric view design, naming conventions, versioning, and documentation, in alignment with Data Governance metadata standards.

• Builds reusable data products in Unity Catalog, catalogued with owner, classification, and lineage, enabling self-service discovery without ad-hoc engineering intervention.
• Works from data product specifications and acceptance criteria entering through the Informatics intake process, and flags specification gaps before build work begins.
• Partners with Analytics & BI to ensure metric views meet Direct Lake consumption requirements, so dashboards and reports are built on governed definitions rather than re-derived logic.
• Partners with Partner Data Services on metric views serving external partner feeds, ensuring feed-facing definitions meet contract schema and quality requirements.

• Documents metric definitions, promotion logic, and data products to team standards, and contributes plain-language definitions to the business glossary, ensuring no semantic layer asset depends on a single point of failure.
• Implements validation and observability for semantic layer assets, ensuring metric changes are versioned, tested, and communicated before downstream consumers are affected.
• Partners with QA on data-layer validation of analytics outputs against governance-defined quality dimensions.
• Serves as the senior escalation point for metric definition conflicts, working with business stakeholders and Data Governance to resolve competing definitions into a single canonical version.
• Mentors Analytics Engineers on semantic layer design, SQL and PySpark craft, and documentation discipline; reviews pull requests in Azure Dev Ops & Git to maintain code quality.
• Serves as a technical liaison with business stakeholders, translating business metric requirements into precise, testable definitions and explaining definition decisions in plain language.
• Collaborates with Data Engineering on platform architecture decisions affecting the semantic layer, and with Data Governance on metadata, classification, and lineage standards.

• 6+ years of progressive analytics engineering or data engineering experience, including…