1. Design, develop, and implement data pipelines on AWS using services such as AWS Glue, AWS Data Pipeline, AWS Lambda, AWS Batch, Amazon S3, Amazon Redshift, and related technologies.
2. Demonstrate strong expertise in Amazon RDS and cloud-based database solutions.
3. Design, implement, and optimize Snowflake data warehouse solutions, including data modeling, data loading, transformation, and performance tuning.
4. Collaborate with Data Engineers, Business Analysts, and business stakeholders to understand data requirements and design scalable data solutions.
5. Build data ingestion pipelines to collect data from various sources, including:
- Databases
- APIs
- SharePoint
- SFTP
- Excel files
- Cloud applications

- Develop and maintain ETL/ELT workflows using AWS services and Snowflake.




- Optimize and fine-tune data pipelines for performance, scalability, reliability, and cost efficiency.
- Ensure data quality and integrity throughout the data lifecycle by implementing validation, cleansing, and monitoring mechanisms.
- Monitor and troubleshoot data pipeline issues, identify bottlenecks, and implement corrective actions.
- Implement security best practices to ensure data privacy, compliance, and governance standards.
- Document technical specifications, deployment procedures, and operational guidelines.
- Stay updated on AWS, Snowflake, and contemporary data engineering best practices and recommend innovative solutions.

📌 AWS Snowflake Engineer (Noida)
🏢 Capgemini
📍 Noida