Bharath Kumar Email & Phone Number

New York, New York, US

• Designed and managed scalable storage solutions using GCP Cloud Storage, optimizing data organization, retrieval, and lifecycle management for cost-effective handling of large-scale structured and unstructured data.
• Optimized complex queries on BigQuery for large-scale datasets, reducing processing time and enhancing performance.
• Integrated machine learning models using Vertex-AI for automated predictions and insights.
• Developed scalable data lakes using GCP Cloud Storage for managing both structured and unstructured data.
• Orchestrated data workflows with Apache Airflow on Google Composer to automate and streamline ETL processes.
• Designed real-time data streaming pipelines using Pub/Sub to facilitate seamless data ingestion and integration.

New York, NY, US

• Developed and maintained distributed data processing systems using Apache Hadoop, Spark, and Kafka, supporting real-time and batch analytics for 1 billion+ daily records.
• Migrated on-premises data infrastructure to Google Cloud Platform (GCP), leveraging BigQuery for enhanced performance and cost savings.
• Built ETL workflows using Talend, Airflow, and later integrated tools like Stitch and Fivetran to automate data ingestion.
• Integrated Snowflake into the data pipeline, improving query response times by 30% and enhancing scalability for future data growth.
• Optimized Google BigQuery to handle large-scale datasets, improving query efficiency and reducing processing times by 25%.
• Implemented Delta Lake for efficient handling of ACID transactions in the data lake, improving data reliability and analytics workflows.insights and supporting business analytics.

San Francisco, California, US

• Engineered high-performance data processing solutions in Scala, leveraging functional programming paradigms to enhance scalability and streamline data transformation tasks.
• Utilized Scala’s concurrency features to build asynchronous, non-blocking data workflows, ensuring efficient processing of large volumes of data in real-time environments.
• Created reusable data manipulation libraries in Scala, enabling consistent data transformation logic across multiple projects and improving development efficiency.
• Built complex data pipelines in PySpark to handle data cleansing, transformation, and aggregation, achieving significant reductions in processing times for large datasets.
• Optimized PySpark jobs through tuning and configuration, using advanced techniques to minimize execution time and resource consumption in distributed environments.
• Implemented real-time streaming applications in PySpark, allowing for continuous data ingestion and processing, which supported dynamic analytics and reporting needs.

Bangalore, Karnataka, IN

• Built and managed ETL pipelines using SSIS to extract data from Oracle and MySQL, transform it with custom scripts, and load it into a SQL Server data warehouse, supporting robust downstream analytics.
• Enhanced database performance through careful query optimization, creating indexed views, partitioning large tables, and analyzing execution plans in both Oracle and MySQL environments.
• Developed and maintained stored procedures and triggers in PL/SQL and T-SQL, handling complex data transformations and automating data workflows for batch processing.
• Created and managed dimensional data models with star and snowflake schemas, aligning with business needs to support efficient reporting in a data warehouse setting.
• Engineered data pipelines for structured and unstructured data using Python and shell scripts, ensuring proper data transformation and loading into both staging and production environments.
• Designed and maintained data marts within SQL Server, aggregating data and creating optimized views to enhance reporting and analytics capabilities.

Master Of Science - Ms, Computer Science

Bachelor Of Technology - Btech, Electrical And Electronics Engineering