Kumar K Email & Phone Number

United States

Johnston Ri

-> Led the design and development of comprehensive data pipelines, leveraging Azure services such as HDInsight, Data Lake, Databricks, Blob Storage, and Synapse to efficiently process and manage large datasets.-> Directed the ingestion and transformation of data using Azure Data Factory, automating workflows to enhance operational efficiency and scalability.-> Architected and optimized ETL pipelines in Azure Databricks using Spark SQL and Delta Live Tables, driving insights into customer usage patterns and improving decision-making.-> Integrated Azure Functions with Cosmos DB to facilitate real-time data operations, delivering enhanced application performance and scalability.-> Automated cloud deployments with PowerShell scripts, minimizing manual intervention and ensuring deployment consistency across environments.-> Utilized Azure DevOps and GitHub for continuous integration and deployment (CI/CD), streamlining development workflows and maintaining robust version control.

Rochester, Minnesota, United States

-> Designed and deployed scalable AWS data pipelines utilizing services such as EC2, S3, RDS, Lambda, and Redshift, ensuring high availability and real-time data ingestion for critical healthcare applications.-> Engineered efficient AWS Lambda functions in Python to process and transform complex nested JSON data, supporting streamlined analytics and reporting.-> Developed and optimized Spark applications using Scala for managing and processing data from RDBMS and streaming sources, integrating these with AWS Glue for scalable ETL workflows.-> Built real-time data ingestion solutions using Spark Streaming, transforming and aggregating data from AWS S3, ensuring the timely availability of key insights for healthcare services.-> Automated workflow orchestration using Airflow to manage Spark/Scala job executions, enhancing the efficiency of complex data transformation pipelines.-> Created data-driven visualizations with Tableau, improving data accessibility and aiding decision-making processes for healthcare stakeholders.

Frisco, Texas, United States

-> Automated data pipelines using Azure Data Factory, enabling seamless integration between cloud-based and on-premises systems, driving real-time analytics and operational efficiencies.-> Leveraged Azure Stream Analytics to process and analyze streaming data in real-time, uncovering actionable insights that informed strategic business decisions.-> Utilized REST APIs to access and analyze data from HBase, enabling efficient data retrieval and transformation to support advanced analytics.-> Migrated extensive datasets from RDBMS to Hive tables using Sqoop and implemented incremental data ingestion with Flume and Kafka for real-time data processing.-> Partnered closely with data scientists and product managers to translate data insights into actionable strategies that enhanced performance and operations.-> Developed interactive and insightful Tableau dashboards to visualize key metrics, providing executives with a clear view of business performance.

Boston, Massachusetts, United States

-> Managed the migration of data between Oracle databases and HDFS using Sqoop, enhancing data accessibility and improving the efficiency of reporting workflows.-> Designed and implemented large-scale data processing systems using MapReduce and Hive, optimizing workflows for data transformation and aggregation across distributed environments.-> Led the development of real-time data pipelines using Kafka, migrating legacy streaming systems to a modern AWS infrastructure with Dockerized microservices.-> Built and managed Spark applications for processing data from RDBMS and streaming sources, leveraging Oozie for automation of ETL tasks and job scheduling.-> Optimized Hive queries by implementing advanced partitioning and bucketing strategies, significantly improving query performance and data retrieval times.-> Maintained and scaled Hadoop/HBase clusters on AWS EC2 and EMR, ensuring system reliability and high availability for large-scale data processing.

India

-> Extracted and transformed data from Oracle databases and flat files, ensuring data integrity and compliance with business requirements before loading it into Oracle systems.-> Developed and maintained Informatica PowerCenter mappings, automating ETL processes and optimizing data integration across multiple environments.-> Automated ETL workflows using SSIS, streamlining data migration between SQL Server and Excel, which improved operational efficiency and reduced manual errors.-> Utilized SQL queries to optimize the extraction, transformation, and loading of data, significantly improving query performance and minimizing system downtime.-> Designed and generated comprehensive reports using the Siebel Data Warehouse, facilitating informed decision-making through accurate data analysis.-> Authored and maintained detailed technical documentation for ETL processes, ensuring consistency and compliance across data workflows and systems.