Prasanth Kumar K Email & Phone Number

Indianapolis, In, Us

United States

Gathered business requirements, conducted analysis, and designed various data products.Developed Spark scripts using Python shell commands and implemented data pipelines using Spark transformations and Python APIs on AWS clusters.Designed and developed Spark workflows in Scala to pull data from AWS S3 and Snowflake, applying necessary transformations.Created Spark code in Python and SparkSQL for efficient data processing, leveraging in-memory computation with Spark RDDs.Built key business metrics, visualizations, and dashboards using Tableau.Developed ETL processes using Spark DataFrames to extract, transform, and load data from various sources, including JSON and relational databases.Created Hive tables for storing processed data in a structured format.Analyzed and translated SQL scripts into PySpark implementations for optimized data processing.Performed data transformations, cleaning, and filtering using Hive and MapReduce, loading the final data into HDFS.Generated CSV data files through Python scripting and SQL queries for data extraction, transformation, and loading tasks.Conducted data analysis and profiling in both dimensional and relational data warehouses using complex SQL queries.Followed Agile methodologies throughout the project lifecycle.

Nashville, Tennessee, United States

Gathered and refined requirements with business users to adapt to changing needs.Developed Spark applications using Scala and Python (PySpark) for data enrichment, aggregation, and real-time processing, leveraging SparkSQL and RDDs for in-memory computations.Created complex data processing workflows using Scala scripts, UDFs, Hive queries, and MapReduce, integrating data back into RDBMS using Sqoop.Built ETL pipelines with Spark DataFrames to extract, transform, and load data from diverse sources (JSON, RDBMS) into HDFS and cloud environments.Configured Apache Airflow for data orchestration and Azure services for data migration, including Azure Data Lake, Data Factory, and SQL Data Warehouse.Developed dashboards and visualizations using Tableau and Power BI, including DAX queries for advanced reporting.Created Python scripts for data extraction and transformation with AWS S3, DynamoDB, and Snowflake.Used Git for version control, Jira for project management, and followed Agile practices in SCRUM.Analyzed SQL scripts and data from various sources, applying data profiling and quality metrics to ensure accurate insights.

Chicago, Illinois, United States

Gathered business requirements, conducted analysis, and designed data solutions to meet evolving needs.Developed Spark applications using Scala and Python for large-scale data transformations, denormalization, and data quality checks.Converted Hive and SQL queries into RDD transformations in Spark, optimizing data processing workflows.Created and optimized Hive tables, queries, and data partitioning for enhanced performance.Led the migration of on-premises data (Oracle, SQL Server, DB2, MongoDB) to Azure Data Lake using Azure Data Factory (ADF V1/V2).Designed solutions and developed Spark scripts on Azure HDInsight for data aggregation, validation, and performance optimization.Utilized Informatica PowerCenter for ETL processes, loading data from diverse sources into target databases.Developed MapReduce programs to process semi-structured and unstructured data, including XML and JSON files.Created Python scripts to read data from AWS S3, processing CSV, JSON, and Parquet files, and loading into DynamoDB and Snowflake.Worked with NoSQL databases like HBase, creating tables to manage large volumes of semi-structured data.Actively participated in daily SCRUM meetings, contributing to team productivity and project progress.

Bentonville, Arkansas, United States

Conducted data analysis, profiling, and requirement analysis to support data-driven decisions.Developed Spark applications using Scala and Python for data quality checks, enrichment of clickstream data, and transformation of Hive/SQL queries into RDD operations.Utilized Spark Streaming for batch processing of real-time data and automated processes for flattening JSON data from Cassandra using Hive UDFs.Optimized MapReduce jobs with efficient HDFS usage and compression techniques.Managed Hadoop log files and developed Python scripts for SQL vulnerability checks, including SQL injection and permission analysis.Created and managed Hive tables, writing Hive UDFs for complex data transformations and aggregation.Designed NoSQL schemas in HBase and implemented MapReduce programs for processing semi-structured and unstructured data like XML, JSON, and Avro files.Worked in Agile and SCRUM environments, contributing to continuous integration and participating in walkthroughs and inspection meetings to monitor project progress.

Hyderabad, Telangana, India

Gathered business requirements, conducted analysis, and designed data products to meet project objectives.Developed Spark scripts using Python and implemented data pipelines for big data processing with Spark transformations and AWS clusters.Designed and developed Spark workflows in Scala for data extraction from AWS S3 and Snowflake, applying necessary transformations.Built Spark applications using Python and SparkSQL for efficient data processing, in-memory computation, and RDD management.Created visualizations, dashboards, and reports using Tableau to present key business metrics.Developed ETL processes using Spark DataFrames to extract, transform, and load data from diverse sources, including JSON and relational databases.Created Hive tables to store processed results and utilized Hive, MapReduce, and HDFS for data transformations, cleaning, and filtering.Analyzed SQL scripts and implemented solutions using PySpark for optimized data processing.Worked with complex SQL queries for data analysis and profiling in dimensional and relational data warehouses.Followed Agile methodology throughout the project lifecycle to ensure continuous delivery and improvement.