Antony Raj V

• Developed and maintained various Snowflake database objects, including warehouses, schemas, tables, views, streams, tasks, file formats, and stored procedures to support data warehousing and analytics requirements.

• Collaborated with cross-functional teams, including business analysts, data scientists, and reporting teams, to understand data requirements and deliver scalable, high-performance, and optimized data solutions aligned with business needs.

• Designed and implemented data ingestion workflows for structured (CSV) and semi-structured (JSON, Parquet) data from AWS S3 using Snowpipe and Snowflake staging mechanisms to support both real-time and batch data processing.

• Designed and implemented Snowflake Streams and Task Trees to manage incremental data loads, track data changes, and consistently capture DML operations for downstream analytics and backup requirements.

• Performed Snowflake query and warehouse performance optimization by monitoring resource utilization, analyzing workloads, and applying best practices to improve processing efficiency and control costs.

• Implemented data ingestion pipelines using Snowpipe, Streaming APIs, and bulk data loading mechanisms to load data from cloud storage, including AWS S3, into Snowflake.

• Collaborated with DevOps and Cloud teams to deploy, configure, and maintain Snowflake environments across multi-cloud architectures.

• Developed and maintained end-to-end automated data pipelines using Snowpipe and Snowflake Streams to support critical investment banking operations, including real-time trading, settlements, and risk assessment workflows.

• Engineered scalable and efficient data ingestion processes from AWS S3 for both structured and semi-structured data, ensuring data accuracy, integrity, and availability across downstream systems.

• Optimized Snowflake schemas, views, and table designs by implementing appropriate clustering keys and partitioning strategies to improve query performance for high-volume financial datasets.

• Utilized Oracle SQL and Snowflake SQL to design, develop, and execute data migration and validation scripts, ensuring data consistency and integrity throughout transition phases.

• Tuned complex SQL queries and ETL workflows to improve data processing efficiency, reduce query execution time, and optimize compute resource utilization.

• Implemented structured and auditable data migration processes using the COPY command and intermediate staging layers, applying required transformations and validations before loading data into production.

• Supported UAT and production environments by conducting performance testing, troubleshooting data-related issues, and resolving production issues to maintain system availability and reliability.

• Developed and maintained Snowflake database objects, including tables, views, stages, file formats, streams, tasks, and stored procedures to support data warehousing and analytics requirements.

• Designed and implemented scalable data ingestion and transformation pipelines using Snowpipe, COPY command, and Snowflake SQL to process structured and semi-structured data.

• Developed and optimized Fact and Dimension tables, complex SQL queries, and data transformation processes to improve data quality and query performance.

• Performed data validation, troubleshooting, and production support for Snowflake pipelines, collaborating with business and technical teams to deliver reliable data solutions.