About the role

Responsibilities:

Lead the design, end-to-end development, and governance of scalable data pipelines, enterprise data warehouses, and data lakes aligned with pharmaceutical distribution models.
You will drive system migrations, optimize large-scale data systems for cost and performance, and partner closely with data scientists, analysts, and engineering teams to deliver production-grade analytics solutions.
Enterprise Architecture and ETL: Architect and manage scalable ETL/ELT pipelines, data lakes, and warehouses using Databricks to process large-scale structured and unstructured datasets.
Performance Tuning and Optimization: Deep-dive into database bottlenecks, tune complex SQL queries, optimize data retrieval speeds, and minimize processing costs.
Governance and Regulatory Compliance: Enforce enterprise data governance, validation checks, error-handling protocols, audit compliance, and quarantine workflows to meet strict healthcare/pharma standards.
System Integration and Migrations: Lead data onboarding from various sources and interfaces into central repositories; guide cross-functional teams during upgrades and cloud migrations.
BI and Operational Continuity: Support BI platforms (reporting, supply chain metrics, predictive patterns) and author standard operating procedures (SOPs) and source-to-target mappings.

Requirements:

Experience Required: 7+ years of hands-on data engineering experience.
Bachelor's degree in computer science, statistics, IT, or equivalent (required).
Master's degree in data engineering, computer science, or information systems (preferred).
Work Experience: 7+ years in enterprise-level data pipeline development, architectural design, and production deployment. Regulated industry (pharma/healthcare/life sciences) background is a strong plus.

Required Certifications:

Preferred Certifications:

Technical Stack:

Data Engineer