- Manage a team of data engineer to automate ML algorithms for personalized Hardware upgrade offer and offer price for each user for on device ad units, my offer, email and web. This increases device sales, increase revenue, decrease churn and improve operational efficiency of campaigns by 25%.- Collaborate with cross functional team to define data requirement and provide data solutions.- Design/Review distributed scalable reliable solutions to extract, transform and load data pipelines using distributed technologies and automate ML models for generating insights.- Ensure data quality, integrity and security through data lifecycle.- Collaborated with advertisement teams to create actionable insights from raw data sets.

- Created Customer LifeTime Value model for daily cohorts analyzing the Subscription/Advertisement Monetized user pattern and predicting future cohort size revenues for each monetized source for existing and future cohorts.- Developed the algorithms to measure data-driven attribution models for TRC users browsing behavior - capable of assigning credits to individual touch points in a customer’s streaming journey.- Implemented a fully-automated pipeline to fit attribution models on a daily basis at which analyze 80TB of log data to determine efficacy of advertising campaigns.- Developed similarity measures and visualizations for active Roku channels and active content available on The Roku Channel.

- Architect, design and develop data discovery tools for all resources/assets.The tool creates a unique resource catalog across platforms, determining cost, ownership, lineage, expected life time. It also offered visibility into the real cost of services by attributing the cost of platforms used by them. - Developed a client performance aggregation metrics which collects data from client applications such as android, ios, tv, web devices using spark, hadoop, druid, tableau. The metrics intended to measure end user quality of experience and standardization across all platforms.

Global Business Intelligence group at Apple IS&T is responsible for managing all the Reporting Data Warehouses, development of new reports with changing business needs, and managing data induction, transformations base on business needs etc. Apple GBI (Global Business Intelligence) reporting enhancement project is for building reporting structure for Apple ITMS (iTunes Store) Sales, Marketing and Finance teams.Technical Roles and Responsibilities :- Architect and Develop the application using various frameworks and languages such as Spark, Hadoop, Hive, Java, Python, Scala, PL/SQL, and Unix shell scripting and following the Agile Methodology.- Work with Spark, Hadoop, Hive, Oozie, Cassandra, Sqoop and other Hadoop ecosystem components in a migration project from Teradata to Hadoop.- Develop solutions using different file formats/serdes like ORC, Parquet and exporting them in Avro/Json schema- Develop Spark Applications for generating insights.- Create UDFs/UDAFs in Hive.- Create Oozie workflows to execute Hive queries and UDFs through incrementally scheduled jobs using Autosys- Use join strategies and partitioning of large tables for significant performance improvement- Optimize and tune Hive queries, Map-Reduce and UDFs- Resolve issues raised in productionOther Initiatives :- Migrated Hive based ETL pipelines to Spark- Develop customized java actions for oozie

Working on Big Data like Hadoop, Hbase, Hive, Apache PIG, Flume, Sqoop and overall 9+ yrs exp in Java/J2EE, Oracle, MySQL, AWS EC2, S3, Elastic MapReduce, Web Services, distributed and parallel computing application for BFSI, Retail etc

Worked on setup of reporting data storage so that data ingress can be analyzed for boosting overall business promotion and operation like weather briefing, finding the purchase trends of fuel products, analysis of various planned trip in respect of learning and better handling in future. These reports are then egress and published to dashboard for business decision.

Worked on a real time data collection and storage and injection and analysis for fraud detection. Worked on technologies Google App Engine, Data Store.

Worked on end to end web based J2EE applications.