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Strong employer brand, metro location, and senior role increase competition but specialized skills narrow candidate pool.
Core data engineering skills transfer across industries, though life-sciences compliance experience is preferred, making fit moderately sensitive.
Explicit 10+ years, master's degree, and mandatory Snowflake/dbt/AWS/compliance skills create high shortlisting rigor.
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Lead design and delivery of scalable, secure cloud-native data pipelines and AI-embedded data products on AWS and Snowflake for rare disease innovation.
Implement AI-accelerated development including AI copilots for code/test generation, automated documentation, and data quality observability with anomaly detection and self-healing capabilities.
Own governance and compliance controls for data platforms ensuring adherence to GDPR, HIPAA, FAIR, and TRUSTed data principles; mentor engineers on responsible AI use and modern data engineering practices.
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, and resilient solutions.
Strong hands-on expertise with SQL, Python, ETL/ELT (Apache Airflow, AWS Glue), Snowflake (including advanced features), dbt, and AI tools for data engineering.
Location: Bangalore (Manyata Tech Park); preference for local candidates who can join immediately.
Experienced in designing and optimizing cloud-native data engineering platforms with AI integration, especially on AWS and Snowflake.
Skilled in practical use of AI copilots and AI-enabled data quality/observability to enhance engineering efficiency and reliability.
Demonstrated leadership in mentoring engineers on best practices for responsible AI and data governance within regulated, life sciences environments.