Snowflake, PySpark and Cassandra Professional

• Design, develop, and maintain scalable big data solutions using Snowflake, PySpark, and Cassandra technologies.

• Build and optimize data pipelines for batch and real-time processing using distributed computing frameworks.

• Develop ETL/ELT workflows to support enterprise data integration and analytics requirements.

• Work with Snowflake data warehouse to design efficient data models, schemas, and performance-optimized queries.

• Implement PySpark-based data processing solutions for large-scale data transformation and analytics.

• Manage and optimize Cassandra NoSQL databases for high availability, scalability, and performance.

• Collaborate with cross-functional teams to gather data requirements and translate them into technical solutions.

• Ensure data quality, consistency, and governance across all data engineering processes.

• Monitor and tune data pipelines for performance optimization, cost efficiency, and reliability.

• Participate in code reviews, debugging, and troubleshooting data engineering issues.

• Work with cloud platforms and distributed systems to deploy and manage data solutions.

• Follow best practices for CI/CD, version control, and data engineering standards.