Mani Kumar Email & Phone Number

Led End-to-End Data Migration & Transformation:- Successfully migrated and transformed 800+ objects totaling 4TB from SQL Server to Snowflake, optimizing data processing capabilities for Sams Club.Success Metrics: Achieved a 30% increase in processing speed by implementing Spark code using Scala and Spark-SQL/Streaming. Enabled seamless data migration from various sources like AWS Redshift, Oracle, MongoDB, and SQL Server, enhancing data accessibility and boosting brand's technological prowess.Architected and Implemented Large-Scale Data Intelligence Solutions:-Designed and developed a robust data warehousing solution using Snowflake, integrating AWS, Kafka, Spark, Scala, and various big data technologies, to align with Sams Club's analytical needs.Success Metrics: Reduced data access time by 25% through intelligent query streamlining and implementing Redis to support Snowflake. Enhanced data sharing between two Snowflake accounts, strengthening internal collaboration and establishing a reputation for innovative data management solutions within the industry.Developed Real-Time Stream Processing Applications & APIs:-Created a real-time stream processing application using Spark, Kafka, Scala, and Hive for Streaming ETL, and developed internal APIs with Node.js, MongoDB, Python, Flask, and Django to enhance the user interface and operational efficiency.Success Metrics: Achieved a 20% increase in real-time data processing capabilities and contributed to a 15% growth in user engagement on the internal platforms. This development positioned Sams Club as a frontrunner in technological innovation, enhancing brand recognition and trust within the market.

Vernon Hills, Illinois, United States

Architected and Implemented Large-Scale Data Solutions:-Led the architectural design and operationalization of a comprehensive Snowflake Cloud Data Warehouse, migrating over 100 datasets using WhereScape.-Successfully transitioned key on-premises systems to Azure Cloud Services, enabling a more robust and agile data infrastructure.-Resulted in a 35% improvement in data processing efficiency, facilitating faster decision-making processes and enhancing the brand's reputation for leveraging cutting-edge technology.Enhanced Data Visualization and Reporting Capabilities:-Designed and created multiple business-centric dashboards using Tableau and PowerBI, integrating data from various sources through Azure Data Lake Analytics/Store and HDInsight.-Coordinated with BI teams to export analyzed data for visualization, generating insightful reports that influenced key business strategies.-The initiative drove a 25% increase in user engagement with data-driven insights, showcasing the brand's commitment to leveraging data analytics for informed decision-making.Developed and Optimized Data Processing and Integration:-Pioneered the development of microservices and REST APIs for data integration, employing technologies such as Apache Kafka, Spark, Hive, Pig, and Python.-Utilized AVRO format for efficient data ingestion and implemented performance tuning for Redshift tables.-Successfully completed migration from on-premise data sources to Azure Data Lake and Storage using Azure Data Factory.-This strategic development led to a 40% reduction in data latency and a 20% increase in data consistency, underlining the brand's focus on quality and performance in data management.

St Petersburg, Florida, United States

-Successfully designed and implemented a robust ETL process using Informatica which streamlined the ingestion of data from various sources such as Flat Files and Excel into the Oracle Data Warehouse. This optimized process resulted in a 15% increase in data processing speed, thereby enhancing the responsiveness of data-driven brand awareness strategies.-Spearheaded the automation of data ingestion jobs from FTP servers into Hive using Oozie workflows and developed Python utility tools for enhanced HDFS table validation. Additionally, executed continuous integration and development practices via Azure DevOps which improved code version consistency by 20% and accelerated the workflow efficiencies, ultimately bolstering brand awareness initiatives by ensuring up-to-date and reliable data for Raymond James Financial Services.- Architected and maintained a high-performance data pipeline in Microsoft Azure, while also leveraging Azure Spark Databricks to expose transformed data in parquet formats for efficient storage. Further enriched data insights by creating interactive business decision-making graphs using Python's matplotlib library, leading to a 10% uplift in stakeholder engagement and reinforcing brand awareness with data-driven insights.

Hyderabad, Telangana, India

-Tuned and optimized AWS Redshift by effectively utilizing distkey and sortkey, leading to a 25% increase in query performance, enhancing the efficiency of cloud solutions in line with NISUM's innovation initiatives.- Developed and implemented Kafka consumers to channel data from Kafka into Cassandra, enabling near real-time analysis, supporting NISUM's drive for immediate insights and responsive data handling.-Installed and configured key Hadoop components including Map Reduce, HDFS, and Hive, and developed multiple preprocessing MapReduce jobs using Java and Scala. This enabled a 30% improvement in data cleaning efficiency, aligning with NISUM's goal for robust data management solutions.-

Hyderabad, Telangana, India

- Utilized ERWIN to redesign and restructure Logical and Physical Data Models, resulting in a more coherent and efficient data architecture, contributing to a 20% improvement in database performance in line with ICICI's drive for operational excellence.-Designed and implemented ETL specification documents using Informatica PowerCenter, streamlining the data extraction, transformation, and loading process. This improved data integrity and reduced processing time by 15%, supporting ICICI's commitment to reliable and efficient data management.-Led efforts in data profiling, validation, and integration, along with the creation of materialized views, boosting query performance by 18%. This reinforced ICICI's reputation for delivering precise and timely data analytics, enhancing customer trust and brand loyalty.