Amit Pradhan

Developing the pipeline for organizing and analyzing the data in different file formats from source catered. Developed and handled performance, supplier scorecard, quality, ARES and cross market components in SPInE. Deciding load strategies for data pipelines. Creating data models for the objects to be developed. Based on the data volume, Identifying the memory/core configurations required for the Driver and Executors, and the partitioning/re-partitioning to be used. Applying transformation logic using Spark CORE, Spark SQL and Data Frames. Deciding and creating jobs and execution plans on Oozie. Worked in platform team for spark codes and job optimizations. Worked on Hive for data analysis and defect resolution.

Analyzing the source data in GCP in different formats. Developed the pipelines for SCITS, GTS, IBP, Inventory, BOM, ECN, Product Characteristics modules. Analyzing the Source System data to fix in case of any file structure deviation. Creating the aggregated and consumption layer based on the calculations required. Developing code using PySpark, Dremio and SAP HANA. Creating workflows and scheduling the jobs in Automic. Deciding the configurations for data proc clusters for each job. Optimizing the pipelines for reducing cloud cost. Worked on Big Query for data analysis.

BGI is a research platform for portfolio managers divisions where they consume pre-existing and newly incorporated trial Vendor Feeds for decision making. It also involves creation of Final feeds based on PM/CPM inputs and requirements over the trial feeds using spark core and Data Frames. Analyzing raw data from the feed to identify the file structure in case of missing Source System Analysis docs. Identifying the memory/core configurations required for the Driver and Executors, and the partitioning/re-partitioning to be used. Creation of generators at different levels using Spark CORE and Data Frames to onboard trial feeds to the DAP platform. Importing data from Oracle database to HDFS using SQOOP. Applying transformation logic using Spark CORE, Hive and Data Frames as per the PM, CPM teams’ requirement. Documenting the feed details in Confluence. Facilitating the weekly testing and release management for the deployments. Identifying the common practices across feeds to automate and improve the Bug fixes and defect resolution. Provide production support if required.

The purpose of the project is to store, analyze and process the data from income tax return. Information generated is stored in Oracle database and processed as client’s requirements. Engaged in Oracle PL/SQL development of stored procedures and packages in all phases of SDLC to optimize the existing system and enhance the code to comply with the client's dynamic requirements. Involved in ETL support role and helped automate most activities along with performance tuning of the existing codes to double the throughput of intimations of IT returns generated per day. Developed Assessment year 2016-17 and 2017-18 changes for all the ITR Types as per the Indian Government Rules. Developed & automated communication (245 notice & reminder) between income tax department and tax payer or assessing officer for adjustment of current assessment year refund with prior years of demand. Developed threading approach for all communications to expedite the performance. Ensured effective knowledge sharing in the team and reduced dependencies.