Rohit Phadtare

Tech stack: Apache spark with Scala, PySpark with Pandas and Numpy, Impala, Unix scripting, Control M, Delta Lake, Azure Data bricks, Azure Data Factory, Azure Synapse, Azure DevOps for Iac and CI/CD etc.

• Designed and implemented big data solutions to store, process and analyse large and complex datasets which helped to successfully adopt 120+ regulatory reports on new system so far
  
• Implemented complex data pipelines in ADF by using Spark dataframe API's and SQL by applying semantics on different types of external data sources like RDBMS, CSV, JSON, PARQUET files which helped to improve QlikView application performance
  
• Tuned and optimized existing spark jobs by different techniques like in-memory cache, dynamic resource allocation of executors, usage of narrow transformations etc. to ensure they are running efficiently and effectively. As a result, daily batch execution overall performance has been improved by 30%
  
• As lead of onshore L3 support team , mainly responsible for performance of big data systems, identify potential issues, and troubleshoot problems in UAT and PROD.
  
• Did orchestration of entire project's data flow through control-m and then migrated same to Azure Data Factory
  
• Implemented proof of concepts with help of Azure Databricks, Azure Data Factory and Azure Synapse for specific requirements from external users to support external applications and deployed fully to run in production by building ADF data flow

• Tech stack: Apache spark - Core, SQL and GraphX using Java & Scala, Hive, HDFS, PostgreSQL and PL/SQL, Rest API, Docker
  
• Acted as expert technical lead to programming staff in program development, testing and implementation process
• Revamped risk calculator module within 6 months that exceeded performance expectations

• Tech stack: Apache Spark with scala, Hive, Impala, My-SQL, Team City etc.
• Performed root cause analysis to provide resolutions for production issues.
• Individually managed to resolve 30 critical pending tickets in single month to support production when team was short of resources by designing unix shell
  scripts to gather and update metadata dynamically

• Tech stack: Hadoop, SQOOP, Hive, Oracle 11G, Java, Selenium API, Apache spark, OOZIE
• Implemented big data solutions and migrated successfully from Oracle to Hive to consolidate around 50 data marts under one application.
• Received 'Value Award' for designing & development of desktop application named as ‘Requester Authorization Portal' to automate requester authorization process for support team which saved up to 2 hrs of every team member on daily basis.