-Having around 8+ years of professional expertise in Data-Driven approaches to solving diverse business problems using big data, analytics, and implementation of parallel processing.-Experience in Hadoop Ecosystems HDFS (Storage), Spark, Map Reduce (Processing), Hive, Pig, Sqoop, YARN, AWS, Job Tracker, Task Tracker, Name Node, Data Node, Apache, Cassandra, and MapReduce programming paradigm.-Expertise in the AWS Stack, which includes AWS, SNOWFLAKE, C2, S3, LAMBDA, DATA PIPELINE, EMR, SNS, Cloud Watch, AWS-REDSHIFT, DMS, and ATHENA. Practical experience using the AWS family of services, including EC2, Amazon RDS, VPC, IAM, Amazon Elastic Load Balancing, Auto Scaling, CloudFront, SES, and SQS.-Expertise in building CI/CD on AWS environment using AWS Code Commit, Code Build, Code Deploy, and Code Pipeline and experience in using AWS CloudFormation, API Gateway, and AWS Lambda in automation and securing the infrastructure on AWS.-Experience on Migrating SQL database to Azure data Lake, Azure data lake Analytics, Azure SQL Database, Data Bricks and Azure SQL Data warehouse and Controlling and granting database access and Migrating On premise databases to Azure Data lake store using Azure Data factory.-Adept in statistical programming languages like R and Python including Big Data Technologies like Hadoop 2, HIVE, HDFS, MapReduce, and Spark.-Experience in Database Design and development with Business Intelligence using SQL Server, Integration Services (SSIS), DTS Packages, SQL Server Analysis Services (SSAS), DAX, OLAP Cubes, Star Schema and Snowflake Schema.-Expertise in Tableau and Power BI, I design interactive dashboards using features like Calculated Fields and SQL. Experienced in code automation, crafting customized reports, and transforming complex data into visually clear insights for informed decision-making.-Processed real-time data using Kafka 0.10.1 and Kinesis, funneling results into S3 Data Lake. Automated Kafka cluster infrastructure creation with Terraform, tailoring instances and storage dynamically across AWS regions and availability zones.-Extremely capable of handling big data sets that are structured, semi-structured, or unstructured, facilitating Big Data and machine learning applications. HBase, Cassandra, and MongoDB NoSQL database experience and created Sqoop scripts for data migration from Teradata and Oracle to Big Data Environment.