varanasi Rohit

Designed and implemented modular ETL frameworks using AWS Glue, Snowflake, and dbt, enabling scalable and reusable data processing components. Engineered end-to-end pipelines integrating PySpark, dbt, and Snowflake, ensuring seamless ingestion from diverse financial systems.

Designed and implemented scalable ETL platform on Azure using Snowflake as the core data warehouse, driving improved data integration and accelerating insights delivery. Developed and managed data integration workflows to load data from various sources into Snowflake using tools like Snowpipe, ETL/ELT frameworks, and third-party connectors.

Worked on AWS Glue, S3, EMR for the migration process and involved in creating Hive tables, Partitioning, loading, and analyzing data using Hive queries. Used Spark APIs to perform necessary transformations and actions for building the data model as per the requirement.

Created Databricks jobs using Spark Scala code and processed streaming data through Spark jobs where the source was Kafka. Executed Spark jobs on cleaned data to calculate cumulative user investments on a daily and overall basis.

Developed and designed new applications based on detailed business requirements, ensuring alignment with organizational objectives. Optimized existing applications for enhanced performance, scalability, and user experience.

Specialized in Business Analytics, focusing on data-driven decision-making and analytical methodologies. Gained expertise in leveraging data for strategic business insights.

Majored in Electrical and Communications Engineering, building a strong foundation in technology and engineering principles. Developed skills in various aspects of information technology.