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Work Background
AmazonSoftware Development Manager, Amazon Music Division
Jul. 2020San Francisco, California, United StatesAmazon is a multinational technology company with 1.5M+ employees and $574.8B in revenue in 2023. It operates Amazon Music, a music streaming platform and digital music store with 55M+ subscribers. In my role, I drive several initiatives to improve data quality and integrity for Amazon Music. My team developed an IQR-based data quality technique, reducing manual monitoring, decreasing false alerts by 43%, and cutting data processing latency from 26 to 4 hours. We also introduced 5 new APIs to tackle critical issues like validation errors and event volume inaccuracies. By enforcing schema checks, I ensured 100% network traffic validation without extra costs, which marked a first since 2018, and cut infrastructure expenses by 63%. I led the migration of on-premise hosts to AWS, reducing needed capacity by 33% and saving 62% in infrastructure costs. By introducing the Data Validation Dashboard, I’ve decreased financially impacting data errors from 6.9B to 300M and subsequently reduced the on-call ticket backlog by 90%. Through strategic planning and system deprecation, I achieved hundreds of thousands of dollars in savings. Beyond the technicalities of my role, I excelled in managing and developing our people. Under my leadership, I’ve expanded our team's global presence into 3 continents, including the USA, India, and Mexico. I fostered a culture of continuous development that reduced attrition by 90% and significantly enhanced team performance.
Indeed.comSr. Software Engineer Lead
Jan. 2019 - Jul. 2020San Francisco, California, United StatesIndeed is the world's #1 job site, serving over 350 million visitors monthly across more than 60 countries. As a Senior Software Engineer Lead, I focused on improving the user search experience and fulfilling business objectives through innovative data processing solutions. I led the revamp of our data processing pipelines utilizing technologies such as Hadoop, BigData distribution systems, and Spark. This initiative boosted data recency by 40%, streamlined the data flow, and supported more informed decision-making processes. I was also instrumental in the professional development of junior engineers, guiding them through mentoring and a commitment to continuous performance improvement. This not only elevated their productivity but also enhanced team effectiveness. Additionally, I took charge of documenting project progress and refining operational procedures, including runbooks and playbooks for risk management. These efforts ensured clear communication with stakeholders and improved our team's readiness and efficiency in handling future incidents.
Lore IO (Acquired by Alteryx)Founding Engineer/Engineering Manager
Feb. 2016 - Jan. 2019Sunnyvale, California, United StatesLore IO is a collaborative data transformation platform serving industries with AI-driven data analytics solutions. During this time, I led the development of Lore Cloud, from inception to launch and enhancement. Through my efforts, I’ve scaled our infrastructure to manage 100+ TB of data, which subsequently enhanced our product’s market entry. I oversaw the design and implementation of scalable big data solutions, including a transition to a fully managed Hadoop cluster. This move resulted in a 99% uptime for our cloud infrastructure. My initiatives also led to the modernization of our data pipeline systems and enhanced cloud infrastructure scalability through the adoption of a Jenkins-based management system. Therefore, improving resource utilization and operational visibility. I prioritized security by integrating LDAP authentication and Kerberos-based encryption, ensuring secure access to our cloud services. By identifying emerging technological trends, I contributed to the development of a scalable, high-performance data architecture that supported advanced analytics and machine learning applications. Moreover, I built and developed a multidisciplinary engineering team of 15 members, through skill enhancement and promoting a culture of continuous learning, which elevated our innovation capabilities and adaptation to new technologies.
Walmart eCommerceStaff Software Engineer
Jun. 2013 - Feb. 2016Sunnyvale, California, United StatesMy role involved enhancing the company's software systems for better performance and user experience. I developed and secured patents for 3 MapReduce algorithms that advanced the analysis of customer logs. This improved our understanding of customer behaviors through sessionization and graph analysis. Additionally, this innovation provided valuable insights that informed strategic decisions and enhanced data analytics. I also led a team of 5 engineers and 2 ML data scientists to create and launch a tool capable of processing 2+ TB of data daily. This effort significantly boosted Walmart’s search analytics and user experiences. Furthermore, I architected a tool for the merchandising team, enabling real-time discovery of business opportunities during the holiday season. These contributions were instrumental in streamlining data processing and leveraging analytics for business growth.
MyCityWayData Scientist
Mar. 2013 - May. 2013Manhattan, New York, United StatesMyCityWay is a mobile technology partner for global brands, offering a platform to optimize mobile strategies and enhance customer engagement across various digital touchpoints. In this capacity, I’ve designed and implemented advanced data analysis and machine learning models to enable personalized, context-based insights and services within the MyCityWay ecosystem.
University of Arkansas at Little RockResearch Assistant
Jan. 2012 - Feb. 2013Little Rock, Arkansas AreaThe aim of the project is to develop a distributed graph management system for billion connections scale graphs. Hadoop served the base platform for the proposed graph management system. The project is supported by Acxiom corp., USA under the supervision of Dr. Kevin Liles, Technical Unit Leader at Acxiom Corp., Prof. Xiaowei Xu, UALR, AR, USA.
Outcomes:
• Storage Structure: Designed a distributed storage schema with an indexing mechanism to boost network elements search capability. • Data Placement: An effective solution for network elements balancing by treating high degree vertices distinctly with low degree vertices.
• Efficient Access: Inspired from congestion control mechanism in TCP protocol, a mechanism to distribute requests among available machines in HDFS to prevent congestion at data nodes.
• Efficient Algorithms: Developing of essential network algorithms such as community detection and connected components that successfully address “the curse of skewed distribution” using a dynamic parent-child job based solution. The solution is being published at AINA 2013 conference.
• Patched Apache’s Hadoop source code for congestion prevention and balancing.
• MapReduce implementation of SCAN network clustering algorithm is developed and the results are being published at AINA 2013 conference.
• Processed complete Twitter user-follower network (41 million users and 1.4 billion connections) in just 30 machines within 6 days overtaking other researchers approaches for the same.
• The graph management system is about to be made available to public and investigative analysis will be communicated to relevant conference in near future.
University of Arkansas at Little RockResearch Assistant
May. 2011 - Dec. 2011Little Rock, Arkansas AreaThe aim of the project is to develop a next generation search engine in particular entity based question answering system. The project is supported by Acxiom corp., USA under the supervision of Dr. Hemant Joshi, Former Data Scientist at Acxiom Corp., Prof. Xiaowei Xu, UALR, AR, USA.
Outcomes:
• Processed and indexed 25TB of unstructured raw web data (500 million web pages) using Apache’s Lemur.
• Developed technologies to construct a semantic network from query related documents from the indexed data repository.
• Incorporated SCAN network clustering algorithm to rank entities in entity-entity, entity-sentence semantic network.
• The results from the experiments and evaluations are presented in Text Retrieval Conference (TREC) 2011.
• Public version of the search engine is available at http://www.ualr.edu/vxmartha/softwares.html.
• The documentation of the project is communicated through Asian Information Retrieval Conference (AIRS) 2012.
NCTR FDAResearch Assistant
Jan. 2011 - Dec. 2011Jefferson, ARThe aim of the project is to develop technologies to combine gene networks collected from several resources. The project is partially funded by FDA, USA under the supervision of Dr. Weida Tong, Director, NCTR, FDA, Prof. Xiaowei Xu, UALR, AR, USA. The developed technologies have been used and made public at FDA’s site located as http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.
Responsibilities:
Collected gene network data from various public resources.
Extracted, Transformed and Loaded (ETL) the data into a graph database neo4j (a Java based graph database system).
Developed graph algorithms for cluster analysis and significance tests in Java.
Outcomes:
• Investigated several technologies in aggregating more than one networks without losing generality.
• Developed a concise mechanism to combine gene networks from several resources.
• Evaluated the aggregated gene network for significance of the approach with the help of SCAN network clustering.
• The developed technologies have been used and made public at FDA’s site located as http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm. The approach is to presented at MCBIOS 2011 conference and published at BMC Bioinformatics 2011 Journal.
University of Arkansas at Little RockTeaching Assistant
Jan. 2010 - Dec. 2010Little Rock, Arkansas AreaResponsibilities include teaching courses, preparing course material, instructing in lab sessions, taking examinations and evaluating assignments. The courses include Programming methodologies and Database Systems advised by Prof. Srini Ramaswamy and Prof. Xiaowei Xu respectively.
University of HyderabadResearch Staff
Oct. 2008 - Jan. 2010Hyderabad Area, IndiaThe aim of the project is to investigate model based intrusion detection systems to university networks. The project is funded by UGC, India under the supervision of Prof. Hrushikesha Mohanty.
Outcomes:
• Modeled a mechanism to define security policies for Linux.
• Discovered a mechanism to hook an Intrusion Detection System (IDS) for Linux 2.6 to constantly monitor, detect and alert users of possible attacks.
• Developed a full-fledged user friendly gui based application to specify security policies without much efforts from a user.
• The developments are published in two reputed conferences.
University of HyderabadTeaching Assistant
Jul. 2008 - Dec. 2008Hyderabad Area, IndiaTaught Internet technologies course, preparing course material, instructing in lab sessions, taking examinations and evaluating assignments. The course was supervised by Asst. Prof. R.P. Lal and Nagamani, University of Hyderabad, India.
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