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    Home»Blog»Bitthal Khaitan: An Industry voice on Cloud and Data Engineering
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    Bitthal Khaitan: An Industry voice on Cloud and Data Engineering

    Syed QasimBy Syed QasimApril 19, 2024No Comments3 Mins Read
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    In today’s dynamic technology world, the combination of cloud computing and data engineering has catalyzed key breakthroughs across industries. Healthcare is one prominent industry that is going through a significant technological transformation. Cloud data engineers, like Bitthal Khaitan, a Top Data Engineering Voice on Linkedin, are using their expertise to propel innovation, enhance patient care, and streamline operations. He has made significant contributions to the healthcare industry with his 13 years of experience and love for healthcare data, especially in the USA, where the market for cloud data management services alone was valued at $3.9 billion in 2020, while the industry was valued at an astounding $12.9 billion globally in the same year. With a compound annual growth rate (CAGR) of 27.6%, the cloud data management industry is expected to reach a global valuation of $70.9 billion by 2027. The widespread use of artificial intelligence (AI) and data-driven decision-making in organizations across the globe has been largely attributed to cloud data engineering.

    Bitthal is currently employed with CVS Health, a well-known Fortune #10 healthcare solutions provider in the US, as a Lead Data Engineer. Throughout his more than five years at CVS, Khaitan has been instrumental in spearheading projects that make use of healthcare data. He does this by utilizing a flexible technological stack that consists of Google Cloud, Teradata, Big Data, Hadoop, Spark, Python. Data Engineers in CVS are known to have a substantial impact on lowering claims adjudication errors, increasing specialty drug referral conversions, promoting patient adherence to specialty medications, and guaranteeing compliance with federal laws like HIPAA by creating innovative solutions on enterprise datalake platforms on cloud.

    During his 8-year tenure with Tata Consultancy Services, Asia’s #1 IT company, he made significant contributions to their Healthcare clients like Kaiser Permanente, Davita and Cigna by developing and maintaining their datawarehouse platforms resulting in improved operations, lowered costs, and better patient experience. With its strong Indian roots, Bitthal contributes invaluable knowledge to the international healthcare sector. His article on the potential for Cloud Data Engineering-driven AI solutions to transform the Indian healthcare industry was just released on the esteemed and official Artificial Intelligence website of the Government of India. The piece demonstrates his in-depth comprehension and familiarity with the Indian healthcare sector and how technology may be a vital tool in resolving the problems that the sector is facing.

    Regarded as an expert in cloud data engineering, Khaitan is a respected technology professional. He was recently highlighted on the famous billboards in New York Times Square as a top 1% mentor on Topmate.io, a platform where mentors & mentees connect. He has received recognition on a global scale after being bestowed with the esteemed “International Achievers’ Award 2023”. The Indian Achievers Forum bestows this prestigious award to honor exceptional career accomplishments made on or after 2000.

    With more than 30,000 LinkedIn followers and millions of views on his content, Khaitan has made a name for himself as a preeminent thought leader and his influence goes beyond his position at CVS Health as a senior cloud data engineer. Khaitan actively steers the technological improvements in the business as a member of IEEE, British Computer Society, and member of the tech advisory board at Packt, a UK based technical book publishing firm. As a technical reviewer, Bitthal reviewed 2 technical books on Cloud Data engineering for Packt. He’s a highly sought-after voice in the worldwide tech community due to his sharp views and knowledge.

    Data Engineering
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    Syed Qasim

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