● Recruited and managed a brand-new team of data and business analysts to support Salesforce's Marketing cloud usage-based-product analytics and insights.● Led architecting and consolidation of product usage data sources into a single unified cloud data lake on AWS, resulting in over $255k in annual savings and improving data visibility by 90%.● Developed a product usage analytics tool that allowed a quantitative approach to understanding the customer lifecycle (Marketing, Customer Acquisition, Sales, Product Adoption, Value Realization, Upsell/ Cross-sell, and Renewals) in a holistic fashion, reducing the sales lifecycle from 3 months to 2 weeks.● Drive Product Analytics and Insights roadmap to scale expertise and use of product-usage data in decision-making across the customer & product lifecycle.

● Built and developed data infrastructure from scratch to support Salesforce's backend Infrastructure related analytics and data science initiatives, ingesting the right data across 5 diverse primary sources into a data lake, helping data analysts and data scientists be more productive in handling business needs, improving our Time-to-Insight/Action/Deployment, as well as return on analytics (ROA) by 80%● Processed raw application logs (~3TB / day) for facilitating an early warning system product which achieved an incremental revenue of ~1.5B and huge customer success and retention.● Drive self-serve and data literacy across the infrastructure product team by designing and implementing a one-stop-shop data tool that quickly scaled from 0 to 500 daily active users.

Designed, architect and build a data platform over Big Data Technologies and facilitated insightful daily analyses of website data collected by external sources, spawning recommendations and tips that increased traffic by 38% and margin revenue by 16%.Responsibilities:• Worked on a live 72 nodes Hadoop YARN cluster running CDH5.3 with highly structured and semi-structured data of 90 TB in size (270 TB with a replication factor of 3)• Designed and architect Hive/HBase distributed Data warehouse/Data Hub with data being extracted from Exadata and Teradata into HDFS using Sqoop.• Created and architect Python-based API for managing all Hotel Platform data across the hotel ecosystem and build a hotel data repository to be used for BI, Revenue Management, Reporting, Customer Analytics, and Pricing.• Created and worked Sqoop jobs with incremental load to populate Hive External tables for BI reporting using Tableau via Cloudera Impala. Lead a team of report/viz engineers and own the complete lifecycle of Hotwire visual analytical applications, from the development of mock-ups and storyboards to complete production-ready applications.• Extensive experience in writing Pig scripts to pre-process and transform raw data from Salesforce.com and Omniture Web logs into forming baseline data.• Implemented Dynamic /Static Partitions, and Bucketing concepts in Hive and designed both Managed and External tables in Hive to optimize performance. • Solved performance issues in Hive and Pig scripts with an understanding of Joins, Group, and aggregation and how it translates to MapReduce jobs.• Developed Oozie workflow for scheduling and orchestrating the ELT process within the Cloudera Hadoop system.• Applied the architectural and engineering concepts to design Big Data solutions using R, Spark, and Hadoop by collaborating with the internal Data Science team.