Snowflake Data Engineer - Clinical & Life Sciences (India Remote)

As a Strategic Planning & Implementation Partner for global companies, CloudLabs Inc has evolved into a transformative partner for Business Acceleration Advisory, Transformative Application Development & Managed Services. With a team of 250+ experienced specialists and offices in the US, Canada, Australia & India, CloudLabs is now at an inflection point and ready for its next curve of progress. Key Responsibilities: - Build and automate end-to-end data pipelines using Python and Snowflake (including Snowpark and Streams/Tasks) to ingest diverse clinical trial data feeds. - Design, develop, and maintain secure, scalable data pipelines extracting data from Veeva Safety/Vault APIs into Snowflake. - Design scalable data models in Snowflake that support complex R&D queries, ensuring alignment with industry standards (like CDISC SDTM/ADaM). - Architect optimal Snowflake data models (schemas, tables, views) tailored for life sciences compliance and safety reporting. - Partner closely with R&D data scientists to prepare, clean, and optimize features for machine learning and statistical modeling. - Write and optimize complex SQL queries, stored procedures, and Snowpark/Python scripts for high-performance data processing. - Maintain strict data governance, ensuring all pipelines comply with HIPAA, GxP, and clinical trial data privacy regulations. Required Qualifications: - 5+ years of hands-on experience with Snowflake architecture, advanced SQL, Snowpipe, performance tuning, and query optimization. - Strong proficiency in Python (pandas, API integrations, and Snowpark). - Deep understanding of clinical trial data structures, electronic data capture (EDC) systems, or clinical data management systems (CDMS). - Proven experience working with Veeva Vault APIs, Veeva Safety, or Veeva Vault Loader. - Proven experience with orchestration tools and building robust error-handling into data pipelines. - Familiarity with Life Sciences, specifically Pharmacovigilance (PV), drug safety, or GxP compliance data. - Familiarity with Snowpark Python or standard data schemas like CDISC. As a Strategic Planning & Implementation Partner for global companies, CloudLabs Inc has evolved into a transformative partner for Business Acceleration Advisory, Transformative Application Development & Managed Services. With a team of 250+ experienced specialists and offices in the US, Canada, Australia & India, CloudLabs is now at an inflection point and ready for its next curve of progress. Key Responsibilities: - Build and automate end-to-end data pipelines using Python and Snowflake (including Snowpark and Streams/Tasks) to ingest diverse clinical trial data feeds. - Design, develop, and maintain secure, scalable data pipelines extracting data from Veeva Safety/Vault APIs into Snowflake. - Design scalable data models in Snowflake that support complex R&D queries, ensuring alignment with industry standards (like CDISC SDTM/ADaM). - Architect optimal Snowflake data models (schemas, tables, views) tailored for life sciences compliance and safety reporting. - Partner closely with R&D data scientists to prepare, clean, and optimize features for machine learning and statistical modeling. - Write and optimize complex SQL queries, stored procedures, and Snowpark/Python scripts for high-performance data processing. - Maintain strict data governance, ensuring all pipelines comply with HIPAA, GxP, and clinical trial data privacy regulations. Required Qualifications: - 5+ years of hands-on experience with Snowflake architecture, advanced SQL, Snowpipe, performance tuning, and query optimization. - Strong proficiency in Python (pandas, API integrations, and Snowpark). - Deep understanding of clinical trial data structures, electronic data capture (EDC) systems, or clinical data management systems (CDMS). - Proven experience working with Veeva Vault APIs, Veeva Safety, or Veeva Vault Loader. - Proven experience with orchestration tools and building robust error-handling into data pipelines. - Familiarity with Life Sciences, specifically Pharmacovigilance (PV), drug safety, or GxP compliance data. - Familiarity with Snowpark Python or standard data schemas like CDISC.