Client/Project - Grubhub Inc. Data League • Involved in the design and development of AWS hosted distributed compute analytic platform known as GDP (Grubhub Data Platform). GDP is based on decoupled persistent storage (s3) and ephemeral distributed compute (EMR). Platform leverages open source technologies wherever possible, including Hive and Presto as the distributed SQL engine, Re:Dash as the SQL UI, Azkaban as the job orchestration application and Jenkins for automated deployment of spark code and Azkaban workflows. For data ingestion platform relies on Spark and MR (Aegisthus to ingest Cassandra backups). • My responsibilities in the GDP involves: - Design and development of various workflows using Spark (PySpark) for data ingestion and data integration. - Platform Development which includes integrating new data sources and development of Azkaban templates and plugins. - Platform Maintenance which involves - Upgrading tools, Automated deployment and Production Support). • Design and development of the horizontally scalable ETL platform using Celery and RabbitMQ. An ETL platform that moves data from MySQL, PostgreSQL, MS SQL Server, FTP/SFTP. S3 and Apache Cassandra into our data warehouse on Amazon Redshift using MapReduce, Hive, Python and command line tools. The scripts also regularly communicate with APIs and get data from FTP and SFTP servers as well as network drives and can alert recipients through email or instant messaging. • Completed PoC to process data in a real time using Apache Spark Streaming and Kafka with Databricks Notebook. • Responsible for Onsite co-ordination, production deployment, and production support team. • Designing, creating, optimizing, and maintaining multiple databases and data warehouses such as one on Redshift, as well as many other smaller DBs that we create for specific purposes. • Using and being proficient with multiple tools on Amazon Web Services, especially S3, EC2, RDS, Redshift, and EMR.

Client/Project: Undertone - UDMS (Jan 2014 to Feb 2015)• As part of the Undertone UDMS team we analyze and process the undertone ad server log data (request, impression, clicks and events). • Designed and developed a system to pull data from various third parties across many dimensions. This system was deployed on Apache Karaf. After data pull we used to process data using Apache Hadoop and Map Reduce.• Technologies used: Apache Hadoop, Amazon AWS (EMR, Redshift, Data Pipeline, SQS and EC2), Java, Python, Apache camel and Apache Karaf.Client/Project: Santander Consumer USA - Data Development (July 2012 to Oct 2013)• As part of the SCUSA Data Development team we deal with the movement of data (Loan Application Details and SCUSA Customers) across the multiple vendors which validates the application and customer information across various parameters. • Executed PoC to demonstrate the use case of a Big Data using AWS EMR and Hadoop Map Reduce.• Technologies used: SQL Server, Control-M, Powershell and Batch scripts are the main technologies used here.• Additional Roles and responsibilities: - Lead and mentor the junior team members.

Working in EA Olympus Sims3 Telemetry: Designed and Developed ETL (Python) Reporting (MSSQL Server 2008 and SSRS 2008) Sims Medieval Telemetry Designed and Developed ETL (Python)Pydev ( http://pydev.org/ - Eclipse plugin for python development) Enhancement: Developed various feature for EA and contributed back to open source (https://github.com/hussainbohra/Pydev)

EA - GOS Worked as a Python/Java/J2EE Developer for EA GOSEA Olympus - As a Python Developer for reviewboard (http://www.reviewboard.org/) - Sims4 Asset Loading and Reporting (Jasper Reports)

Product Development, Bug Fixing and Technical Support

Working on an NMS Product called Everest. Protocols: SNMP, WMI, Netflow and MPLSProgramming Language: C++ & Python