We had the pleasure of speaking with Deepanjit about his journey, his achievements, and his vision for the future of data-driven decision-making.

Thank you for taking the time to chat with us today, Deepanjit. Before we dive into the specifics of your work, can you tell us a bit about your background and how you got started in Business Intelligence?

Certainly! My journey into Business Intelligence began with a strong foundation in Data Engineering, Data Science, Analytics and Quantitative Methods. I earned my Masters of Science in this field, specializing in Data Science and Data Engineering, from the University of Texas at Dallas, where I was fortunate to receive the Dean’s Excellence Scholarship twice. Alongside my academic achievements, I am honored to have been invited into prestigious societies like Phi Kappa Phi and other international honor societies, which acknowledged my dedication to excellence and achievement. My passion for data was ignited by the potential I saw in using analytics to drive business decisions, which led me to Amazon, where I now lead a global team, spread out across North America, Europe and Asia, responsible for some of the company’s most critical business intelligence and data infrastructure projects.

You’ve achieved a lot in your career so far. Can you share about some of the challenges you faced and how you overcame them?

One of the most transformative challenges I tackled was centralizing Amazon’s core people data business intelligence infrastructure. This initiative aimed to create a unified source of truth by standardizing and consolidating data and analytics across Amazon’s people data services, ensuring consistent and accurate insights for senior leadership, including VPs and above. A key innovation in this project was the implementation of a Continuous Integration/Continuous Deployment (CI/CD) pipeline—a practice typically associated with software development but rarely applied in the Business Intelligence (BI) and Data Engineering space. Introducing CI/CD in this context was transformative, as it automated code integration and deployment, significantly reducing errors and ensuring data consistency. This allowed for faster, more reliable updates and deployments, fundamentally changing how we manage and deliver BI solutions.

To further elevate the system, I led the integration of Generative AI (Gen AI) for both insight generation and data pipeline monitoring. This AI integration was groundbreaking, enabling the automatic extraction of actionable insights from consolidated data and providing Amazon's leadership with a deeper, more nuanced understanding of trends and performance metrics. Additionally, Gen AI continuously monitored data pipelines, quickly identifying and addressing potential issues, thus maintaining data integrity and boosting overall system reliability.

After achieving these milestones, I led the migration of Amazon's payment business intelligence data infrastructure to Amazon Web Services (AWS), a comprehensive cloud computing platform. This complex project required a blend of technical expertise and strategic planning, as any disruption could have had significant repercussions. By leveraging cloud technologies and fostering cross-functional collaboration, we successfully executed the migration, resulting in substantial savings in both headcount and infrastructure costs. This experience underscored the critical importance of agility and foresight in managing large-scale projects and further solidified the transformative impact of modern cloud solutions in the BI and data engineering landscape.

The combined impact of these initiatives led to a more efficient, reliable, and aligned analytics approach, empowering leadership to make confident, data-driven decisions. This innovation not only increased the speed and trusts in our analytics processes but also streamlined operations, reduced cognitive load on leadership, and strengthened collaboration across global teams, ultimately driving better outcomes for the business.

Let’s shift to the core of our discussion. Based on your extensive experience, why do you believe Business Intelligence and Generative AI are crucial in today’s business decision-making, and how should companies leverage them?

Business intelligence and Generative AI are the cornerstones of modern business decision-making. They empower companies to move beyond gut feelings and intuition, providing concrete insights that drive more informed and strategic decisions. At Amazon, these technologies are critical across the business—from optimizing supply chain logistics to enhancing customer experiences. The key is to seamlessly integrate Business Intelligence and Gen AI into the core of business operations, ensuring that data-driven insights and AI-generated predictions inform every major decision. This approach requires not only robust technology and infrastructure but also a culture that values and trusts data and AI-driven insights. By doing so, companies can unlock new levels of efficiency, innovation, and competitive advantage.

From your perspective, what are the key skills that data professionals need to develop to become effective business leaders?

To be an effective business leader in the field of data, one must possess a strong technical foundation combined with strategic thinking. Understanding the intricacies of AI, machine learning, and cloud computing is essential, but it’s equally important to be able to translate these technical capabilities into business value. This involves developing skills in communication, stakeholder management, and project leadership. It’s also crucial to stay connected with the business, understanding its needs, challenges, and goals, so that you can apply data science in ways that truly drive the company forward.

What advice would you give to someone just starting out in the field of Business Intelligence (BI)?

My advice would be to focus on continuous learning and to embrace both the technical and strategic aspects of the field, with a strong emphasis on understanding AI's role in Business Intelligence. As BI continues to evolve rapidly, staying current with the latest tools, technologies, and AI-driven methodologies is crucial. AI is becoming increasingly integral to BI, offering powerful capabilities for predictive analytics, automation, and insight generation. It’s important not only to master these technologies but also to understand how they can be leveraged to create real business value.

At the same time, don’t lose sight of the bigger picture—how your work impacts the business and drives strategic decision-making. AI can amplify your efforts, but it’s your ability to apply it strategically that will set you apart. Finally, don’t shy away from challenges that push you out of your comfort zone. Embracing complex problems will provide the greatest opportunities for learning and professional growth.

Finally, how can our readers stay informed about your work and get in touch with you?

I’m regularly active on LinkedIn, where I post updates on our latest projects and share insights on Business Intelligence, AI, and all things data. I’m always eager to connect with others in the industry, whether you’re an experienced professional or just starting your journey. Additionally, be sure to follow Amazon’s innovation channels, as our team is constantly engaged in projects that are driving the future of data-driven business.

Thank you, Deepanjit, for taking the time to share your knowledge and experiences with us. We wish you continued success at Amazon and in all your future endeavors!