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Senior Software Engineer, Data Platform at Wealthfront
Currently working at Wealthfront as software engineer in Data Platform Infrastructure team Graduated from University at Buffalo with Master's in Computer Science & Engineering at with interests in Computer Networking, Distributed Systems, Big Data and various new Front End Technologies. Summer internship experience at Amazon Web Services in their WorkSpaces Team, developing web based metric dash board to display statistics of user’s successful and failed connection events to their workspaces. Over 3 years of experience in Mphasis, Bangalore India in software development which involved web application development, Proof of concept development for various content management tools like Kofax, Teleform etc in a Scrum based environment.
University at Buffalo
Master of Science (M.S.), Computer Science
January 1, 2014 – January 1, 2016
Birla Institute of Technology and Science, Pilani
Bachelor of Engineering (B.E.)
January 1, 2006 – January 1, 2011
Wealthfront
Senior Software Engineer
December 1, 2019 – Present
Palo Alto, California, United States
Elementum SCM
Software Engineer
August 1, 2017 – December 1, 2019
San Francisco Bay Area
Advertising.com, A Division of AOL Platforms
Backend Software Engineer
May 1, 2016 – July 1, 2017
Palo Alto, California
Amazon Web Services
Software Development Engineer Intern
May 1, 2015 – August 1, 2015
Greater Seattle Area
Mphasis
Software Engineer
June 1, 2011 – May 1, 2014
Greater Bengaluru Area
Group Messenger with Total and FIFO Ordering Guarantees (Java, Android)
May 29, 2026 – Present
The app is a Group Messenger that multicasts a message to all app instances and store them in a permanent key-value storage. (Multicasts also includes the one that is sending the message). The app includes ordering guarantees which covers total ordering as well as FIFO ordering. (Ordering implies the receiving order based on the Lamport logical clocks) The messages were assigned sequence numbers in order to provide total and FIFO ordering guarantees. A content provider is implemented using SQLite on Android to store key-value pair. App uses Basic-multicast. It does not implement Reliable-multicast
Stock Volatality Analysis using Map-Reduce and Hadoop
May 29, 2026 – Present
Used Map-reduce on a Hadoop environment at Center for Computational Research(University at Buffalo) to compute the volatility of 3000 stocks with each having data of three years from 2012 to 2014. Analysis of performance was done using node scaling and data scaling.Three types of data sets where used, small(3000 files),medium(12000 files) and large(40000) files.Each data set was processed using different number of nodes,to determine the scalability of the code.
Amazon Dynamo Style Key-Value Storage (Java, Android)
April 1, 2015 – Present
Developed a simplified version of Dynamo which covers ID space partitioning/re-partitioning, Ring based routing, Node joins, Quorum based replication, recovery from replicated storage after failure. SHA-1 hash function is used to lexically arrange nodes in a ring and find the location for a particular key to be stored. The main goal is to provide both availability and linearizability at the same time. In other words, it should always perform read and write operations successfully even under failures, a read operation should always return the most recent value.
Handwritten Digits Classification through Multilayer Perceptron Neural Network (using Python)
March 1, 2015 – Present
Implemented the multilayer perceptron neural network in evaluating the performance in classifying handwritten digits using 1-of-K coding scheme. Used the MNIST data set which contains 60,000 samples of training data and 10,000 samples of test data. Implemented Neural Network using feed forward and back propagation algorithms. Tuned the hyper-parameters to maximize the accuracy.
Peer to Peer Distributed-Hash-Table based on Chord protocol (Java, Android)
March 1, 2015 – Present
Simple Key-Value storage based on Chord design which is a Ring-based routing architecture for the Nodes(which stores the values) SHA-1 hash function is used to lexically arrange nodes in a ring and find the location for a particular key to be stored. Each node maintains a successor and predecessor pointer for nodes in the ring. Multiple Instanc4. Multiple Instances form a Chord ring and serve insert/query requests in a distributed fashion according to the Chord
Stock Volatility Analysis using Apache Hive and Pig
March 1, 2015 – Present
Used Apache Hive and Pig on a Hadoop environment at Center for Computational Research(University at Buffalo) to compute the volatility of 3000 stocks with each having data of three years from 2012 to 2014. Analysis of performance was done using node scaling and data scaling.Three types of data sets where used, small(3000 files),medium(12000 files) and large(40000) files.Each data set was processed using different number of nodes,to determine the scalability of the code. Performance of Hive and Pig was compared to that of Map-Reduce. It was found that In case of using Pig and Hive the processing time of the data-set decreased from 400 to 4 mins,increasing the performance by approximately 99% than Map-Reduce.
News Personalization
December 1, 2014 – Present
Developed a system that provides personalized news to atleast 3 different users , using Solr, java. It takes user profile and preferences when displaying the search results. It also provides user interface to query and display the results with snippets of information about the news article.
E-mail Forensics with DKIM
November 1, 2014 – Present
Investigated e-mail headers to identify a potential E-mail Spoofing. Analyzed the working of DKIM and PGP in email security. Wrote a C code using Fork – Exec system calls to apply the core DKIM algorithms on an email repository to identify the best combination of encryption and message integrity algorithms based on security provided and the time required for encryption and decryption
Implementation of Routing Protocols (using C and UDP Sockets)
November 1, 2014 – Present
Implemented a simplified version of the Distance Vector Routing protocol using Bellman-Ford algorithm and runs on the top of servers behaving as routers using UDP. Each server runs on a machine at a predefined port number and output their forwarding tables along with the costs and is robust to changes in the link costs. Routing updates are exchanged using UDP periodically and when user gives command to exchange update.For every node in network a separate timer was maintained. If for any node updates are not received for 3 consecutive timeout intervals, the link cost to that node was made infinity.
Web Security and Program Security (WebGoat, Web Sacarb )
October 1, 2014 – Present
Analyzed various injection flaws in Web Security using WebGoat and WebSacarb.
Reliable Transport Protocols
October 1, 2014 – Present
Implement - Alternating-Bit, Go-Back-N and Selective-Repeat in C on UNIX OS. Implemented Multiple timers using single timer for Selective Repeat. Optimizations were done to improve performance. Analyzed performance of the protocols for various loss and corruption probabilities ranging from 0.1 to 0.8
Remote File Sharing System (using C and TCP Sockets on UNIX OS)
September 1, 2014 – Present
Developed a file sharing system among remote hosts over TCP. Its a client server system where clients can upload files and download different files from multiple clients simultaneously. Maintained all transfer statistics like upload / download speed at the server side and analyzed network performance using iPerf
Cultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards distributed systems, data processing, and machine learning, which aligns well with a Big Data Engineer role. The diverse range of projects, from academic implementations of distributed protocols to industry experience with large-scale data platforms, indicates a broad technical curiosity and a willingness to tackle varied challenges. The experience across different companies (Wealthfront, Elementum SCM, Advertising.com, Amazon Web Services) suggests an ability to integrate into various team structures and company cultures. However, the projects are predominantly personal or academic, and while relevant, they don't provide direct insight into collaborative work styles or specific cultural values.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and an ability to work on complex, distributed systems. The experience in various companies suggests adaptability to different technical environments. However, without specific psychometric or communication test results, a detailed assessment of soft skills and operational fit is limited.