Mr. Bhaskar Yakkanti has built his career at the intersection of performance, compliance, and scale in data engineering. With over 12 years of experience, he has led impactful data-driven initiatives across sectors such as hospitality, finance, and customer engagement platforms. His work consistently bridges operational challenges with durable technical solutions, advancing both user experience and enterprise integrity.

As a senior data engineer, he played a pivotal role in developing a centralized customer data platform for a leading leisure services provider. This system unified behavioural and transactional data from diverse channels, enabling personalized experiences and informed decision-making. His contributions ranged from designing ingestion pipelines to implementing validation checkpoints that ensured data trustworthiness and compliance.

In a previous role, he spearheaded the integration of machine learning into loyalty frameworks for a financial services client. The solution is personalized customer rewards in real time, driving engagement and maximizing return on investment. He also contributed to credit card programs that tailored spend-to-earn incentives using predictive algorithms, aligning cardholder behaviour with business objectives.

His published work reinforces his engineering practice. His research explores performance optimization in NoSQL-based reporting, structured streaming architectures for live analytics, and machine learning systems for compliance automation in regulated environments. Each study offers replicable blueprints grounded in field experience, helping other engineers translate theory into practical impact.

He is certified as a GCP Professional Data Engineer and Cloudera Spark & Hadoop Developer and holds a master’s degree in information technology. A mentor to junior engineers and a contributor to global tech communities, he continues to shape scalable, trustworthy data systems that balance speed, precision, and governance.

At IAF, we are pleased to recognize his contributions to the advancement of data engineering and real-time analytics.