Pavan kumar

• Engineered end-to-end data pipelines using Azure Data Factory and Azure Data bricks for diverse sources.
• Optimized ELT processes, transforming various data formats into Azure Data Lake, reducing processing time by 10 hours monthly.
• Achieved 35% reduction in operational costs through optimal job cluster configurations in Azure Data bricks.
• Automated job execution with a generic scheduling pipeline, decreasing manual effort by 10%.
• Deployed Data bricks Lakehouse architecture, enhancing ETL processes and achieving 15% increase in data processing efficiency.
• Collaborated with teams to align business requirements with data engineering best practices.
• Optimized storage and compute usage in Azure Data Lake Storage, saving 20% through lifecycle policies and caching strategies.

Designed parameterized ADF pipeline templates, increasing reusability and reducing development time by 20%.

• Engineered end-to-end data pipelines using Azure Data Factory and Azure Data bricks for diverse sources.
• Onboarded various data formats into Azure Data Lake, streamlining ELT processes and reducing monthly processing time by 10 hours.
• Achieved 35% reduction in operational costs through optimal job cluster configurations in Azure Data bricks.
• Automated job execution with a generic scheduling pipeline, decreasing manual effort by 10%.
• Deployed Data bricks Lakehouse architecture, enhancing ETL processes and increasing data processing efficiency by 15%.
• Collaborated with teams to align business needs with data engineering best practices.
• Optimized Azure Data Lake Storage usage through lifecycle policies and caching strategies, achieving 20% cost savings.
• Developed parameterized pipeline templates in ADF, reducing development time and increasing reusability by 20%.

• Configured patient profiles for data centralization and provisioning in eClinical-elluminate tool.
• Executed study setups, including data source import, mapping, and export to AWS.
• Developed custom reports from Oracle Clinical DB using SQL/SAS queries.
• Validated ETL output data utilizing SAS and various validation tools for integrity checks.
• Led data validation and quality control team in creating and executing test scripts.
• Collaborated with stakeholders to define and document data validation requirements.
• Oversaw daily ETL operations, addressing issues during extract, transform, and load processes.
• Provided technical guidance on ETL mapping and data flow processes to team members.

• Developed custom Scheduled Data Provisioning Tool with SAS and UNIX for rapid data refresh.
• Executed clinical domain development to create SDTM-like datasets per client specifications.
• Conducted domain mapping and validation using SAS, ensuring data accuracy throughout processes.
• Performed snapshot request processes for interim and final analyses according to PDM requests.
• Completed production testing after creation of new snapshots to validate functionality.
• Provided clarifications and solutions to inquiries from study teams promptly.
• Participated in User Acceptance Testing (UAT) of domain development codes to confirm performance.
• Engaged in client conference meetings, contributing agenda items and addressing action items effectively.

• Developed domain code utilizing Informatica, Oracle, and UNIX per Detailed Design Document.
• Reviewed Raw CRF and modules for domain development activities.
• Conducted peer reviews of domain development during unit testing.
• Provided technical support to clients regarding changes and maintenance issues with Data Provisioning.
• Distributed status reports of previous ETL runs to user group.
• Maintained ETL schedules for data provisioning; communicated successful completions to Operations team.
• Executed production support activities independently.
• Converted internal annotation CRFs to FDA Annotated CRFs using Annotated Programme.