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Medium — Tier-1 brand and Bangalore metro attract applicants, but senior niche skillset limits volume.
Medium — core data engineering skills transfer across industries, but pharma compliance and FAIR governance increase domain specificity.
High — explicit 10+ years, detailed tech stack, and compliance/domain requirements create strict filters.
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Lead design and delivery of scalable, secure cloud-native data pipelines and AI-powered data products on AWS and Snowflake to support rare disease innovation.
Implement AI-accelerated development workflows, data quality frameworks with anomaly detection, and governance controls to ensure compliance with GDPR, HIPAA, and FAIR principles.
Mentor engineers in responsible AI use and data engineering best practices, collaborate cross-functionally to enable feature-ready data sets and reproducible pipelines.
Master’s degree in Computer Science, Information Systems, Engineering, or related field.
10+ years of experience in data engineering, data management, and analytics with large-scale, secure, resilient solutions; life sciences experience preferred.
Strong hands-on skills in SQL, Python, ETL/ELT orchestration tools (Apache Airflow, AWS Glue), and Snowflake (including advanced features like Streams/Tasks, tuning, security).
Location: Manyata Tech Park, Bangalore; local candidates who can join immediately are preferred.
Experienced technical leader with deep expertise in cloud-native data platforms and embedding AI in data engineering workflows for operational efficiency and compliance.
Familiarity with regulatory and governance frameworks (GDPR, HIPAA, FAIR) relevant to health/life sciences data products.
Strategic collaborator able to mentor teams and enable cross-disciplinary data science and analytics initiatives in a highly regulated industry.