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Ravi Karan Sharma

Big Data Architect

Big Data Architect at Realogy Holdings Corp.

San Francisco Bay Area

Section title

Ravi Karan Sharma's Email Addresses & Phone Numbers

Ravi Karan Sharma's Work Experience

Realogy Holdings Corp.

Big Data Architect

Emeryville, California, United States


Senior Data Engineer

January 2018 to January 2020

Emeryville, CA


Software Engineer II

September 2015 to January 2018

Emeryville, CA

Ravi Karan Sharma's Education

Somerville School, Noida

High School

1989 to 2002

Ryan International School, Trans Yamuna, New Delhi

All India Senior Secondary Certificate, Science

2002 to 2004

National Institute of Technology Rourkela

Bachelor of Technology (B.Tech.), Computer Science, 3.43/4.00

2005 to 2009

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Ravi Karan Sharma's Estimated Salary Range

About Ravi Karan Sharma's Current Company

Realogy Holdings Corp.

Frequently Asked Questions about Ravi Karan Sharma

What company does Ravi Karan Sharma work for?

Ravi Karan Sharma works for Realogy Holdings Corp.

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Ravi Karan Sharma is Big Data Architect

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Ravi Karan Sharma works in the Information Technology and Services industry.

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Ravi Karan Sharma's colleagues are Dhananjai Shastri, Zhenwang Liu, Jennifer PhD, Pruthvi Shetty, Connor Kojimoto, Chiranjib Ghorai, Monalisa Satpathy, Sriram Krishnamurthy, Michael Zhu, and Matt Goss

About Ravi Karan Sharma

đź“– Summary

Big Data Architect @ Realogy Holdings Corp. Emeryville, California, United StatesSenior Data Engineer @ ZapLabs • Leading the development of an Enterprise Analytics Platform (EAP) which unifies the data needs of Realogy across its 10 brands/Business Units (BUs) through Datalake formation and Data Ingestion pipeline tools• Designed and led the implementation of the Data Ingestion pipeline that provisions interconnected ingestion processes onto AWS for any legacy RDMS Data Source in Realogy• Leading the development of a Data lake provisioning pipeline for all data sources in Realogy on the EAP to cater metadata services, change capture updates, raw uncurated snapshots and master datasets as a platform for engineering teams of each BU with security and encryption policies in S3 using GoLang.• Designed/Developed data pipelines in Spark that unify multiple storage Relational/NoSQL/Soft-Relational technologies in a single data and transformation flow to generate curated and enhanced analytical data stores to create on demand analytical visualizations• Built Scalable API Access through AWS API Gateway/AWS Lambda and Swagger over on demand analytical DBs.• Designed and created Machine Learning development pipeline and infrastructure to automate development, training and prediction of/from ML models hosted with high-availability and scalability. Used ModelDB to log machine learning model metrics for visualization and comparison, as a service in Zaplabs (unit of Realogy)• Creation and maintenance of the DataLake for DataScience-as-a-Platform and other verticals such as Data Engineering and Application Services. Created services and process pipelines for population of data lake, making it searchable and query-able for scalable use-cases, including streaming of relational data from Oracle. From January 2018 to January 2020 (2 years 1 month) Emeryville, CASoftware Engineer II @ Gracenote Worked in their Data Platform Engineering group on core architecture design and development.• Designed/Developed new company-wide AWS based scalable, fault-tolerant subscription-based shared data service pipelines as Scala/Java and Spark apps deployed through containers in Mesos/DCOS to ingest data sources for all Gracenote product verticals communicating via Kafka & Cassandra. [AWS:S3/SQS/Dynamo]• Built from scratch a distributed micro-services architecture in a complete overhaul of technology stack that is highly availabile, flexible to changes, with strict guarantees on QOS and throughput. Few formative services are Elastic Ingestion, Dynamic Equalizer Service and Data Filter Spark Pipeline.• Building & Maintaining CI/CD pipelines in GoCD with embedded testing via AWS CloudFormation deployed on Mesos managed via DCOS.• Design and develop to enhance the music data ingest, transform and match-finder systems in C# on .NET platform for Gracenote from processes handling terabytes of data across Oracle, SQLServer, Hadoop & MongoDB daily across platforms. From September 2015 to January 2018 (2 years 5 months) Emeryville, CAComputer Science Masters Thesis @ University at Buffalo In the field of Information Retrieval and Machine Learning, the topic of the thesis was:Online Techniques to find sub-trending phrases in Streaming Documents:Real world events are almost always being discussed and in some cases, documented, on various popularsocial networks online as hashtags. Hashtags are the Internet’s analogues of topics which are popular among users at the present instant of time. The choice of the text used to represent the hashtag is often highly contextual on some outstanding characteristics of the real world event, and is often derived from vernacular or common parlance and thus incognizant of the central aspects of the real world event. We thus are encountered with many hashtags which though represent the same real world event, but have seemingly unrelated names. This problem of finding definition of a trend is unique in its chief constraint of being dynamic due to constant evolution of the real world event. Thus a procedure to identify the main aspects of a trending event should also be temporally sensitive to shift their result along with the development of the event in the real world with the passage of time. We discuss an approach to identify such candidate representative phrases through identifying trends within trends, to mean that if certain phrases are being observed frequently within a time interval, they must represent a contemporary topic of rising interest among the documents being generated at the time.This technique gives emphasis to various aspects of the trending event which are analogous to sub-events within the main event. One of the cornerstones of the technique is to maintain an online mode of operation, with a methodology to observe and process the incoming stream of documents only once. This also makes it practicable to most real world scenarios where information systems consume feeds from various sources and ingest various forms of metadata to enhance their processes of information extraction. From August 2014 to June 2015 (11 months) Buffalo/Niagara, New York AreaSoftware Engineering Intern @ SmartFocus • Apache Solr Performance Profiling• Apache Solr Schema Curation, Index creation, query optimization, sharding etc.• RESTful API service architecture using Hibernate over core data domain in SQL for customer facing sub-systems• Responsible for developing new functionality and upgrading features of the web search portal. Designed and developed features across all layers of the technology stack.• Established the architecture for application domain data to be exposed through RESTful services to be independently called by all sub-systems within ContentSavv From May 2014 to December 2014 (8 months) Buffalo/Niagara, New York AreaSoftware Engineer @ Wize Commerce [PREVIOUSLY Nextag Inc.,]• Designed and implemented core technology stack for high volume and high performance import infrastructure of products from partners like & currently importing 140 million products in 12 hours on a daily basis. High business value project.• Developed core product classification business logic to integrate product & merchant data across Nextag’s product catalog and provide APIs for the Nextag web application providing categorical & parity data, developed product features on the front-end UI using these APIs.• Completely migrated and configured the Nextag website independently for launch of – Nextag’s Netherland website channel • Designed and developed many high revenue front-end UI features for Search Page and Product page serving millions of visitors per day• Responsible for development of Nextag’s primary User Database infrastructure, handled high impact components like sales history, browsing history and user profile management and end-to-end development of business critical internal tools on Spring web applications• Optimized Nextag’s critical search results webpage speed by using bloom filters to replace database look-ups(100-200ms), Javascript performance and CSS optimizations (200-350ms) etc. to reduce TTFB (Time to First Byte) and TTDC (Time to Document Complete) From May 2011 to July 2013 (2 years 3 months) Gurgaon, Haryana, IndiaSoftware Engineer @ Samsung R&D Institute § CDMA Framework development for Radio Access Technology (RAT) switching for different phone bases (Oct 2010 to May 2011):• Involved in migration and development of RAT handshake between CDMA and various other RAT technologies e.g GSM, LTE etc. for other phone bases for Samsung• Implementation involved modifications on the Telephony Framework in Android to make it RAT aware instead of the stock single RAT implementation in Android at the time.• Modifications from the Phone Application to the Telephone Framework till the Radio Interface Layer (RIL) to support the migrated RAT-aware infrastructure implemented in the earlier 4G project (mentioned below)§ Telephony Framework Development on Android Froyo for LTE(4G) based Smartphone on Android Froyo (April 2010 to Oct 2011): • Designed and developed the feature to persist bearers and data connections between RATs when they change dynamically in the network - for the flagship Samsung device at the time, one of the first smartphones to bear LTE/4G. • Implemented all Inter-RAT handover scenarios. Implemented the System Selection Timer which polls the network elements and scans the network when a high priority RAT is unavailable.§ IPv6 Socket Options and Addressing evaluation on Android Platform (Jan 2010 to March 2010):• Evaluated Android kernel's Dual Stack ability, Android’s Wi-Fi and Data interfaces can be configured to the IPv6 addressing, Successful DNS resolution over such IPv6 configured devices and tunneling support of the kernel.§ Spot Focus implementation in Camera on Android (Jul 2009 to Dec 2009)• Implemented the Spot Focus (Tap to Focus) feature on an Android based phone running on Android Cupcake. • Implemented the complete stack, right from the enhancements in the Camera application to the appending the Camera framework to handle the UI feedback from the application, and till the Hardware Abstraction Layer which was modified to interact with the driver for the Camera Hardware. From July 2009 to May 2011 (1 year 11 months) Bengaluru, Karnataka, India

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In a nutshell

Ravi Karan Sharma's Personality Type

Introversion (I), Sensing (S), Thinking (T), Perceiving (P)

Average Tenure

1 year(s), 8 month(s)

Ravi Karan Sharma's Willingness to Change Jobs



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