=> Involved in the Design, Implementation and Testing of Metadata Driven Serverless ETL Framework for Complete Refresh Tables backed by AWS S3, AWS Lambda, AWS Glue, AWS RDS (Postgresql), AWS Athena and AWS SNS. => Implemented AWS Lambda (Python) to start the Glue ETL Job after checking the Metadata Values as Pre-Check Activity and Another AWS Lambda (Python) for updating the counts of Postgresql and Athena in Metadata Tables. => Implemented AWS Glue (PySpark) to load the text delimited data into Dynamic Frame and loaded the data into S3 Parquet Files and RDS Post Transformation (Adding Surrogate Keys and Date Format Conversion)=> Implemented Python Script to fetch the list of modified partitions in HDFS Location and prepare the parameterized query to trigger spark application job (which fetches the hdfs data from that query)

=> Implemented Data Analysis Code on Spark using Java and Mapreduce - Java => Helped the Data Lake Delivery Team to resolve issues on Database End and involved in Technical Discussions with them to provide solutions for Problem Statement.

=> Implemented Solutions for Real Time Data Processing System on AWS Platform. These include solutionsfor sensor data ingestion, data processing and raw data storage for sensor.=> Implemented Solutions for Batch Data Processing System on AWS Platform. These include solutions fordata storage, data processing and data retrieval processes.=> Implemented Backend System for the Metadata Extraction and Resume/Documents Content Extraction onAWS Platform with full text search feature on Backend process.=> Implemented Learning Proof of Concept for Data Coming into Rabbit MQ and Processed as Java Consumerand Stored Raw data in MongoDB.=> Implemented Learning Proof of Concept for Data Provenance, Data Flow and Data lineage Graphs inApache Atlas for Sqoop, Spark, Hive.

=> Implemented Data Ingestion Module for the Data Lake with the features of ingestion data from RelationalDatabase Management System and Flat Files.=> Loaded the data in Hive as Text Format and Converted into Parquet Format.=> Led the Data Delivery and Analysis (Data Quality Analysis and Data Processing) Team of Media Data Lake.=> Implemented Automated Shell Script for loading data from RBMS to Hadoop via Sqoop and Converting theData from Text Format to Parquet Format via Spark SQL and Hive.=> Involved in the Activities of Data Loading, Data Cleansing, Data Analysis and Debugging Data Issue.=> Implement various Aggregated Data Structures by joining multiple facts and dimension tables as a form ofview in Apache Hive and Ran multiple Data Analysis Queries on Spark SQL, Presto and Hive.

=> Developed Stored Procedures, Functions, Triggers, Cursors, Packages (PL/SQL Programming), ExactTarget Emails called through Oracle Database.=> Developed various Shell Script Jobs which are triggered on Scheduled Manner via Control-M and Cron.=> Involved in setting up three Application Databases and Application Servers as key-person in ApplicationTeam for Database Migration (From Oracle 10g database to 11g and Oracle version 9i/10g to 12c).=> Analyzed the Functional Specifications.=> Point of Contact for the Project Management Activities like Internal Quality Assessment, External QualityAssessment and Final Inspection Process.

=> Trained in Unix, C++ and Oracle PL/SQL from Tata Consultancy Services Ltd.=> Implemented C++ Code in Customer Management Module for Hotel Management System with Platform asUnix and Database as Oracle