Jun 2022 – Present · 3 yrs 9 mos

• Responsible for developing, support and maintenance for ETL (Extract, Transform and Load)
• process using SSIS.
• Designed and implemented a scalable data pipeline using Python to automate the ingestion,
• transformation, and processing of large datasets.
• Integrated various data sources (e.g., SQL, APIs, flat files) into a unified system for downstream
• analytics and reporting.
• Used Airflow to orchestrate, schedule, and monitor data workflows, ensuring seamless and
• automated execution of data pipeline jobs.
• Deployed pipeline components using Jenkins for continuous integration and delivery (CI/CD),
• enabling faster, more reliable updates and maintenance.
• Leveraged libraries such as Pandas, SQLAlchemy, and PySpark to ensure efficient data processing
• and optimization.
• Collaborated with cross-functional teams to ensure the pipeline met business requirements and
• improved data accessibility.
• Enhanced data quality and reliability by introducing validation checks and error-handling
• mechanisms, resulting in a 30% reduction in data processing time.
• Created multiple Mapplets, Workflows, Tasks, database connection using Workflow manager
• Create new SSIS packages and modify existing packages implementing auditing and error handling