Lead Data Engineer - Azure/Snowflake DB/Databricks

Lead Data Engineer

Key Responsibilities Leadership & Collaboration

• Act as the primary contact for GBS in support of Advanced Analytics initiatives.
• Bridge communication between LoB stakeholders and technical teams (AI/ML platforms, IT partners).
• Lead strategic business projects that showcase the impact of Data Engineering and Data Science.
• Engage in senior leadership meetings to champion Data Stewardship, Data Ownership, and Data Engineering Architecture & Execution :
• Serve as the Technical Architect for Data Analytics/Data Science projects.
• Lead and supervise implementation of data engineering best practices, including code optimization, CI/CD, and scalable data pipelines.
• Conduct Proof-of-Concepts (POCs) for emerging technologies and guide analytics teams based on findings.
• Advise business and technical teams on modern data architecture, including Snowflake, Azure, Databricks, and other cloud-native & Functional Leadership :
• Mentor and guide junior and mid-level data engineers.
• Act as a functional lead in cross-functional business and technical engagements.
• Collaborate with global and regional data teams across to ensure consistency and Evangelism & Governance :
• Advocate for enterprise-wide use of Data Engineering, Data Stewardship, and Data Quality practices.
• Promote the value of analytics and data science to business teams and leadership.
• Ensure data governance, compliance, and security best practices in collaboration with internal Skills & Qualifications :
• Bachelors or Masters degree in Computer Science, Engineering, Information Systems, or related field.
• 10+ years of hands-on experience in Data Engineering, including architecture design and implementation.
• Deep expertise with cloud-based platforms such as Snowflake, Databricks, Azure Data Services, and Microsoft Stack.
• Strong experience with data pipeline development, ETL/ELT workflows, and orchestration tools.
• Understanding of machine learning workflows, including integration with AI/ML platforms.
• Experience working with pharma datasets and familiarity with compliance/regulatory environments in the pharmaceutical industry.
• Proven experience in stakeholder management, especially in global matrixed environments.
• Excellent communication, leadership, and cross-functional collaboration Qualifications :
• Experience in a global pharma/healthcare setting, especially working across GBS or corporate headquarters.
• Industry recognition or conference participation in data engineering or pharma analytics.
• Certification in Snowflake, Azure, or Databricks is a plus.
• Familiarity with data cataloging, metadata management, and MDM