Top Pharmaceutical Data Engineering Jobs

Build and operate scalable data pipelines, models, curated datasets, dashboards, and recurring reports for Pharmacy Operations. Translate business requirements into governed analytics solutions, perform deep-dive analysis and root-cause investigations, document metrics and metadata, and promote data quality and best practices. Partner with technical and operational stakeholders while mentoring analysts and supporting standards for modeling, visualization, testing, and maintainability.

Owns enterprise data architecture, modeling standards, platform integration, governance, quality, security, and reusable architecture patterns. Partners with executives, engineering, analytics, security, and governance teams to modernize lakehouse, data mesh, streaming, and data product ecosystems. Leads proofs of concept, architecture reviews, platform recommendations, and AI/ML data enablement while mentoring architects and engineers.

Leads the data engineering team, including hiring, coaching, technical direction, platform architecture, data pipelines, Snowflake warehousing, governance, quality, observability, and incident support. Partners with Data Science, Analytics, Clinical Operations, Biostatistics, and Business Development to deliver trusted data products for clinical operations, asset evaluation, reporting, and machine learning. Oversees budgeting, resourcing, documentation, technical programs, and responsible use of AI engineering tools.

Develop and maintain data sources and SQL databases to support business decisions and VALET metrics reporting. Write and optimize SQL queries, maintain Excel reports, validate and troubleshoot data, and collaborate with IT and stakeholders to design and implement data solutions and communicate findings to technical and non-technical audiences.

Designs and governs PANTHERx’s semantic layer on Databricks, including Unity Catalog metric views, Gold-layer tables, promotion logic, and reusable data products. Establishes canonical, versioned business metrics for BI, analytics, partner feeds, and AI inputs. Responsibilities include data modeling, migration, validation, observability, documentation, governance, stakeholder collaboration, and mentoring analytics engineers. The role requires advanced SQL, Python, and PySpark skills, strong Databricks expertise, and experience operating across analytics engineering and data engineering.

Leads the Analytics Engineering function, owning Databricks semantic layers, Unity Catalog metric views, Gold-layer data marts, Silver-to-Gold promotion logic, and reusable data products. Establishes governance, documentation, architecture, and quality standards while partnering with Data Engineering, BI, Governance, Informatics, and QA. Builds and develops the analytics engineering team, ensuring consistent business metrics across dashboards, partner feeds, internal analytics, and AI model inputs.

Builds, operates, and owns enterprise data warehouse pipelines and models on Databricks. Develops Delta Lake batch and streaming pipelines across Bronze, Silver, and Gold layers; implements data quality, reconciliation, observability, governance, and performance improvements. The role owns assigned data domains, supports event-driven ingestion, documents architecture and runbooks, responds to incidents, collaborates with QA and governance teams, and mentors data engineers.

Leads enterprise strategy, architecture, delivery, governance, and operations across data, analytics, information management, automation, AI, and GenAI. Drives transformation toward governed data foundations, reusable data products, data marketplaces, self-service analytics, and responsible AI. Oversees platforms, pipelines, dashboards, automation initiatives, budgets, vendors, and senior technical teams while partnering with business, Legal, Compliance, Quality, and Security. Builds training, adoption, stewardship, and change-management programs across a global life sciences organization.

Leads Commercial data architecture and technology ownership across Commercial, Medical Affairs, and Patient Services. Defines data strategies, warehouses, data products, master data management, governance, quality standards, and analytics enablement. Partners with business stakeholders, Data & AI teams, vendors, and implementation partners to design scalable solutions using platforms such as Snowflake, Tableau, and Power BI. Provides architecture oversight, supports AI initiatives, manages technical delivery, and ensures data compliance, reliability, and operational sustainability.

Design and govern conceptual, logical, and physical enterprise data models supporting analytics, reporting, AI-ready datasets, and certified data products. Translate business requirements into scalable data structures across customer, product, payer, and territory domains. Establish modeling standards, review models against Common Data Model standards, maintain metadata and lineage accuracy, and resolve data gaps and inconsistencies. Collaborate with business, engineering, and technology stakeholders to provide modeling expertise and design guidance.

Build and maintain end-to-end Microsoft Fabric data engineering and analytics solutions, including lakehouses, warehouses, ELT pipelines, semantic models, Power BI dashboards, and Fabric apps. Develop AI-ready semantic models for Claude, automate audit and data analytics processes, and pilot agentic AI frameworks. Partner with audit stakeholders to translate business needs into governed solutions, lead technical design and standards, manage delivery, and improve adoption, performance, and reliability.

Designs, develops, tests, and maintains scalable data systems, SQL/ETL procedures, reporting processes, and .NET applications supporting pharmacy benefit management. Responsibilities include database performance optimization, query tuning, troubleshooting pharmacy claims and NCPDP submissions, technical design, stakeholder collaboration, Agile participation, cloud integration, mentoring, and recommending reliable engineering solutions. The role requires expertise in SQL Server, data warehousing, dimensional modeling, healthcare data compliance, and pharmacy industry standards.