Lead Data Engineer – Pharma

Location : Hybrid Delhi NCR

Experience : 8–10 years (relevant)

Employment Type : Fulltime

About PCGI

PCGI Consulting is a boutique consulting firm specializing in high-performance business and technology consulting. By blending management consulting expertise with deep technology capabilities and industry experience, we help organizations unlock value from large and complex datasets.

The Role

We are seeking a Lead Pharma Data Engineer to drive data engineering initiatives across commercial life sciences functions. The ideal candidate will combine deep domain knowledge of pharmaceutical data ecosystems with strong technical expertise in Python, SQL, AWS & Dev-Ops to architect, lead and deliver scalable, high-impact data solutions.

Key Responsibilities :

• Lead the design, development and maintenance of data solutions & pipelines to integrate and manage commercial pharma datasets.
• Work with cross-functional teams such as Sales Operations, Marketing Operations, Analytics, Market Access, and Sales Planning to address their data needs and enable insights.
• Collaborate with data architects and business stakeholders to design warehouse schemas and analytical data models.
• Ensure seamless data flow across systems such as MDM, Veeva CRM, Data Warehouses, and Analytical Tools.
• Work with diverse commercial datasets including IQVIA (ICADM, Smart, FIA, DDD, Xponent, PlanTrak), PayerSpine, MMIT, 867 data and other pharma datasets.
• Develop and optimize Python and SQL-based data processing frameworks.
• Write efficient, complex SQL queries using aggregations, window functions, and joins for analysis and enhancements.
• Strong experience in databricks, Snowflake & AWS services (EC2, S3, IAM, RDS, Redshift, Lambda, CloudWatch) to manage data infrastructure and pipelines.
• Apply foundational data warehousing concepts (facts, dimensions, star / snowflake schema) in solution design.
• Contribute to continuous improvement in data quality, performance, and scalability. Lead troubleshooting, performance tuning, and optimization for data systems and pipelines.
• Mentor junior engineers and contribute to code reviews, knowledge sharing, and process improvements.

Required Qualifications :

6–8 years of experience in data engineering within the pharmaceutical or life sciences domain.