Krishna Chaitanya Mandhata

Having an overall experience of over 14 years in Product & Platform development. Experience: 1. Salesforce Marketing Cloud Engineering team: Leading the effort of building low latent, highly scalable Transactional APIs for different Messaging channels (like Push notifications). I have also worked on building Email Seed list APIs that would let partners choose dedicated Email deliverability feature providers to analyze and improve their marketing campaigns. 2. Microsoft STCI Satori & Travel Team(s): Leading the Bing Action Links experiences for Music, Movies and Books segments across different international markets. Worked on Hotels offline data ingestion to trigger rich Travel experiences on Bing. 3. Microsoft Bing Retail team: Contribution to design and building of Retail Catalog covering consumer electronics, home and kitchen appliances and fashion categories. Data is acquired from different source providers, normalized, conflated and published to knowledge graph. Data is used to power Bing Retail search experiences. Also, working on entity to Ads matching, conflation improvements, data quality and metrics. Experience on data ingestion and quality frameworks for the Bing Maps data. 4. Wavecrest Payment Technologies: Contribution to the Payment Platform Team in the areas related to the design and implementation of Decision Engine, ACH Payments, Payment Platform services, etc. Worked on delivering web-based solutions to Reliance Jio payments. 5. Pega Systems: Been a part of the Core Engineering team that worked on building features of web based BPM tool Pega Rules Process Commander. Worked on system management tools and performance improvements of the core engine. 6. Satyam Computers: Worked on different performance profiling tools, maintenance of Travel domain project features and delivering Proof-Of-Concept solutions to web-based applications. Certifications: Sun Certified Java Professional (v5.0) & PRPC Certified System Architect (v5.4) & PRPC Certified Senior System Architect (v5.4) Computing in Data Analytics using R (from coursera.org)