Key Skills:Data Integration, Data Governance, AWS, Informatica, Snowflake, People Management, Gen AI, LLM Ops, Agentic AI
Roles & Responsibilities:
- Drive the implementation of AI-Ready Data frameworks to ensure data is trusted, secure, and AI-consumable at scale.
- Lead and mentor teams across Data Quality, Data Governance, and Data Management functions.
- Architect and build automated data preparation systems using AI-driven solutions and agents.
- Design and develop end-to-end data pipelines for structured and unstructured data.
- Collaborate with global cross-functional teams to enable AI innovation and integration with AI platforms.
- Implement scalable data architectures leveraging AWS, Snowflake, and Informatica.
- Establish data observability, monitoring, and governance frameworks across the data lifecycle.
- Drive adoption of GenAI, LLM Ops, and next-generation AI capabilities within data engineering.
- Ensure data quality, compliance, and regulatory adherence in healthcare/biopharma environments.
- Deliver measurable outcomes by enabling AI-ready data products and platforms.
Experience Required:
- 12 - 20 years of experience in data engineering and data management.
- Strong experience in Data Integration, Data Governance, and enterprise data platforms.
- Hands-on expertise with AWS, Snowflake, and Informatica tools.
- Proven experience in leading and managing high-performing technical teams.
- Experience in building scalable data pipelines and architectures.
- Exposure to GenAI, LLM Ops, or AI-driven data platforms is a plus.
- Strong understanding of data observability, monitoring, and data quality frameworks.
- Experience working in healthcare or biopharma domain is preferred.
- Excellent stakeholder management and cross-functional collaboration skills.
Education:Any Post Graduation
