Senior Data Engineer

7,000 Diseases – 500 Treatments – 1 Rare Pharmacy. PANTHERx is the nation’s largest rare‑disease pharmacy, putting the patient experience at the top of everything we do. We seek inspired, compassionate problem‑solvers who produce high‑quality work, thrive in the ever‑challenging environment of modern medicine, and are committed to superior health outcomes for people living with rare and devastating diseases.

Location: Pittsburgh, PA (Hybrid). Classification: Exempt. Status: Full‑Time. Reports to: Manager, Data Engineering.

Purpose

The Senior Data Engineer builds, operates, and owns the enterprise data warehouse and core data pipelines on PANTHERx’s Databricks platform. This role is responsible for EDW architecture, ingress patterns into Bronze, transformation logic from Bronze to Silver, and Gold harmonization rules, and contributes to the platform’s evolution toward a simplified medallion architecture with event‑driven, low‑latency ingestion.

Responsibilities

• EDW Engineering & Ownership: Design, build, and operate enterprise data warehouse pipelines and data models across the Databricks medallion architecture (Bronze, Silver, Gold); assume ownership of assigned EDW domains, ensuring data model integrity, pipeline reliability, ingestion SLAs, and incident response; lead structured documentation of architecture, transformation logic, and feed SQL; execute data model simplification to consolidate legacy layers with validated output parity.
• Pipeline Development & Streaming: Develop and maintain production Delta Lake pipelines, evolving ingestion from batch watermark patterns to event‑driven architectures using Zerobus Ingestion and Spark Declarative Pipelines; implement row‑level reconciliation, validation checkpoints, and quality gates; build Gold‑layer tables and promotion logic that support Unity Catalog metric views, lineage capture, and access controls; optimize pipeline performance, latency, and compute cost.
• Documentation, Quality & Observability: Document architecture decisions, data models, pipeline logic, and operational runbooks to team standards; operate observability tooling, monitor anomaly detection, triage data reliability incidents, and drive root‑cause remediation; implement data contract validation (ODCS or equivalent) to halt delivery on contract failures.
• Mentorship & Cross‑Functional Collaboration: Mentor Data Engineers on Databricks development patterns, SQL, PySpark, and documentation discipline; review pull requests in Azure DevOps & Git; partner with Data Governance, QA, and Partner Data Services on lineage, metadata, test suites, and feed engineering; work from structured requirements entering through the Informatics intake process and flag gaps before build work begins.

Required Qualifications

• 6+ years of progressive data engineering experience, including production ownership of an enterprise data warehouse or large‑scale transformation pipelines with defined SLAs.
• Deep, hands‑on expertise with Databricks in production: Delta Lake, medallion architecture, Unity Catalog, and pipeline performance optimization.
• Demonstrated data‑warehousing depth: dimensional and harmonized data modeling, conformance and survivorship logic, and operating a warehouse as a production system.
• Advanced SQL and strong PySpark/Python proficiency sufficient to build, review, and optimize complex transformation logic independently.
• Proven experience with Azure data services: Azure Databricks, Azure Data Lake Storage, Azure Data Factory, and CI/CD practices in Azure DevOps.
• Ability to absorb complex, under‑documented systems through structured knowledge transfer and produce durable documentation.
• Strong communication and collaboration skills; able to work directly with QA, Governance, Informatics, and business‑facing teams without an intermediary.

Preferred Qualifications

• Healthcare, specialty pharmacy, or regulated‑industry experience with exposure to clinical or operational data environments.
• Production experience with event‑driven ingestion (Azure Event Hubs, Kafka, or equivalent) consumed via Structured Streaming.
• Familiarity with data contract standards (ODCS or equivalent) and pipeline observability platforms (Monte Carlo or similar).
• Experience with enterprise data catalog tooling (Atlan, Collibra, or equivalent) and designing pipelines as catalogued, governed assets.
• Experience leading through influence: mentoring engineers, setting standards, and driving adoption without formal management authority.
• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field, or equivalent experience.

Work Environment

This position works in a home office and professional office environment. When in‑office, the role routinely uses standard office equipment such as computers, phones, photocopiers, filing cabinets, and fax machines, and communicates via Microsoft Teams.

Physical Demands

The employee is regularly required to sit, see, talk, and hear; frequently required to stand, walk, use hands and fingers to handle or feel, and reach with hands and arms. Visual acuity is necessary for reading and working with data on a screen. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Benefits

• Hybrid, remote, and flexible on‑site work schedules (based on the position).
• Comprehensive medical, dental, vision, health‑savings, and flexible‑spending accounts.
• 401(k) with employer matching.
• Employer‑paid life insurance and short/long‑term disability coverage.
• Employee Assistance Program.
• Generous paid time off for full‑time employees, plus paid holidays.