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About

Balachandar Paulraj is a seasoned data engineering leader with over 15 years of expertise in managing complex projects and driving business growth through innovative data solutions. With 7+ years in management, Balachandar has led data engineering teams at PlayStation and Comcast, optimizing processes, increasing revenue, and saving costs. He has contributed to the industry as a technical reviewer, published IEEE author, and patent holder. At PlayStation, he improved ROI and user engagement, while at Comcast, he enhanced service uptime and operational efficiency. His diverse skills include expertise in Spark, AWS, Databricks, and machine learning. Balachandar Paulraj is an experienced data engineering professional with a proven track record of leadership and technical expertise in the field. Currently working as the Manager of Data Engineering at PlayStation in San Francisco, California, he plays a crucial role in managing the design, development, and deployment of data-driven systems and processes within the company. With over five years of experience at PlayStation, Balachandar oversees complex data engineering projects, utilizing his skills in cloud computing, big data processing, machine learning, and analytics. Before joining PlayStation, Balachandar held a Senior Manager position at Comcast, where he spent five years working on data engineering initiatives in Philadelphia, Pennsylvania. At Comcast, he led teams responsible for large-scale data pipelines, data processing systems, and the integration of big data technologies. His work in this capacity involved significant collaboration with cross-functional teams, ensuring that data systems were scalable, reliable, and optimized for business needs. Earlier in his career, Balachandar worked as a Technical Lead at Standard Chartered Bank in Chennai, India, from 2009 to 2014. In this role, he focused on building and maintaining data solutions for the bank, which included managing databases and overseeing data management systems. His responsibilities at Standard Chartered allowed him to deepen his understanding of complex data architectures and helped him develop an extensive skill set in both technical and leadership aspects of data engineering. Balachandar holds a Bachelor’s degree in Computer Science from Anna University, India, which he completed in 2008. This educational foundation laid the groundwork for his future career in data engineering, providing him with a solid grasp of computer science fundamentals that he has continuously built upon throughout his professional journey. In addition to his academic credentials, Balachandar is highly certified in various data engineering and cloud technologies. He holds three AWS certifications, including those for Big Data and Database Development, which reflect his deep knowledge and hands-on experience with AWS services. He is also certified by Hortonworks as an Apache Spark and Hadoop Developer, showcasing his proficiency in big data technologies. Furthermore, he is a certified Machine Learning Developer, with advanced skills in using data visualization tools such as Tableau for analytical purposes. Balachandar's technical expertise is complemented by his commitment to leadership and management, which is demonstrated through his role in managing large teams and overseeing critical projects at PlayStation and Comcast. He also holds a Leadership Principles certification from Harvard Business School Online, further enhancing his management capabilities. Overall, Balachandar Paulraj's career exemplifies a blend of strong technical acumen, leadership abilities, and a commitment to staying at the forefront of emerging technologies in the data engineering and machine learning fields. His diverse experience across global companies like PlayStation, Comcast, and Standard Chartered has solidified his reputation as a capable leader in the data engineering space.

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Skills

Experience

Manager, Data Engineering

Sony Interactive Entertainment

Apr-2019 to Present
Technical Lead

Standard Chartered Bank

May-2009 to May-2014
Senior Manager, Data Engineering

Comcast

May-2014 to Apr-2019

Education

Anna University, Chennai

B.E in Computer Science

Passout Year: 2008

Publication

  • dott image September, 2024

LEVERAGING MACHINE LEARNING FOR IMPROVED SPAM DETECTION IN ONLINE NETWORKS

This paper proposes an advanced methodology of spam detection by including N-gram tf.idf feature selection and a deep multi-layer perceptron neural network, with further improvement through ...

Innovative Strategies for Optimizing Operational Efficiency in Tech-Driven Organizations

This comprehensive study explores cutting-edge strategies for enhancing operational efficiency in technology-driven organizations. As the business landscape continues to evolve rapidly, comp...

Innovative Strategies for Optimizing Operational Efficiency in Tech-Driven Organizations

This comprehensive study explores cutting-edge strategies for enhancing operational efficiency in technology-driven organizations. As the business landscape continues to evolve rapidly, comp...

Innovative Strategies for Optimizing Operational Efficiency in Tech-Driven Organizations

This comprehensive study explores cutting-edge strategies for enhancing operational efficiency in technology-driven organizations. As the business landscape continues to evolve rapidly, comp...

Building Resilient Data Ingestion Pipelines for Third-Party Vendor Data Integration

In this report, the author provides a review of the design and operation of the resilient data ingestion architecture with a particular emphasis on the issues associated with third-party dat...

Peer-Reviewed Articles

Internal and External Re-keying and the way forward

Side Channel Analysis are the security attacks due to the issues in the implementations. This attack bypasses the mathematical security provided by the cryptographic algorithms. These attacks are broadly categorized into the issues related to architectural of the chip manufacturing, attack due to unwanted leakages like power leakage, acoustic leakage, thermal leakage or electromagnetic leakages, and the issues due to programming vulnerabilities for example the heartbleed bug etc. The architectural related issues are fixed when the newer version of hardware is designed once the vulnerability is found in the earlier version. The programming related attacks are solved by patching the software and updating the code that caused the vulnerability to be exploited. The leakage issues are the ongoing issues since it was first discovered in 1997. Among the various leakage issues, the acoustic and thermal leakages aids in the attack related to power analysis. The Electromagnetic attack boils down to the power analysis issue and hence, it all comes down to the power analysis attack. Since it was discovered, the researchers have suggested the solutions for them but on the other side, they would also be vulnerable again. The Power analysis attacks are mainly classified into Simple Power Analysis (SPA), Differential Power Analysis (DPA), Correlation Power Analysis (CPA), and profiled attacks. Their countermeasures are mainly masking and rekeying apart from architectural changes. The masking has been researched extensively and have been widely implemented countermeasure. However, it comes with a very big overhead. Therefore, the researchers started exploring the rekeying to counter them. Rekeying has been classified mainly into the internal and external rekeying both having its advantages and disadvantages. There is currently no literature available that discusses both in detail. This work surveys the work on both the approaches and suggest the way forward for the researchers of the re-keying.

DEVELOPING A DATA-DRIVEN ARCHITECTURE FOR IMPLEMENTING AI-ENABLED DYNAMIC PRICING STRATEGIES IN THE AUTOMOTIVE INDUSTRY

In the Automotive Industry, dynamic pricing is used a lot to make the most money and hold off the competition. The Automotive industry is using AI to build a data-centric framework that will allow dynamic pricing. This research will look at how they are doing it. Automakers can find out about how customers act, how the market is changing, and how competitors plan to beat them by using complicated formulas and strict data collection methods. The aim of this research is to analyze how dynamic pricing protects prices in various industries, with a particular focus on its application in the automotive industry. In addition, the research will discuss about data-driven design approaches incorporating with artificial intelligence (AI), mainly how these technologies could be used to improve pricing strategies by automating choices and letting prices adjust based on the market. Important things like how to use market trends to our advantage, gather and analyze data, and understand how customers behave, and merchandise sales are the focus areas of the paper. As part of the project, AI could also be used to improve pricing methods. Some of these are prediction analytics, machine learning, and reinforcement learning. We can figure out how to make the most money and guess what prices will be in the future by using algorithms that look at past price data. Finally, the study shows that price strategies that are driven by AI and design that is driven by data can have a big impact on the automotive industry. Businesses in the Automotive industry might be able to boost competition, new ideas, and customer trust by using dynamic pricing systems and staying honest all the way through.

Conference/Seminar/STTP/FDP/Symposium/Workshop

Conference
  • dott image Aug 2024

Ext-NoSQL: A NoSQL Schematics through JSON

Hosted By:

2024 IEEE 12th International Conference on Intelligent Systems (IS) ,

Varna, Varna, Bulgaria

Certificates

Issued : Nov 2022
  • dott image By : Harvard Busines...
  • dott image Event : Leadership Prin...
Leadership Principles
Issued : Jun 2023
  • dott image By : Databricks
  • dott image Event : Databricks Cert...
Databricks Certified Data Engineer Associate
Issued : Jun 2020
  • dott image By : Amazon Web Serv...
AWS Certified Big Data – Specialty