Shanmukha Eeti’s career exemplifies the power of adaptability, continuous learning, and strategic thinking, transitioning from building traditional data warehouses to architecting modern cloud solutions.
Shanmukha Eeti is a seasoned technology professional with wide experience in data engineering, cloud architecture, and digital transformation with over 17 years in the field. Very few walk the evolution path from designing traditional data warehousing systems to building modern data platforms on the cloud to support AI and machine learning workloads. , demonstrating adaptability and a comprehensive understanding of the data landscape.
Q1: What initially influenced you to get into data and technology?
A: My interest in technology started during my Bachelor of Engineering studies, in which I majored in Electronics and Instrumentation. Data fascinated me because it told a story that made changing business decisions possible. Early on, I recognized the potential of data for seamless workability in bringing out insights that often remain hidden in plain sight. This curiosity grew into a career focused on using data tools and Modern cloud technologies to optimize business outcomes and support digital transformation.
Q2: Over a decade into the profession, what has been your biggest project to date?
A: One of the most exciting and significant project I led was for Citizens Bank, where I played a pivotal role in envisioning and implementing an enterprise data lake to support critical business functions. I was responsible for designing and overseeing the migration of ETL pipelines from on-premise systems to the AWS Cloud, ensuring the new architecture could handle substantial volumes of transactional data while maintaining data integrity. This project was not just about data migration; it involved reshaping the organization’s entire data strategy. Its success was due to perseverance, hard work, and effective teamwork.
Q3: Would you care to share with us your ‘aha’ moment turning point if you will-where you changed your approach to technology?
A: While working at Thermo Fisher as a Data Engineer, the turning point came when I was asked to design and implement an operational data store for real-time data using AWS services. The experience not only whetted my skills in cloud technologies but also taught me the essence of adaptability with the said innovations-continuous-and that is when I fully adopted the might of cloud-based solutions with modern data architectures to derive business value.
Q4: As someone proficient in multiple cloud platforms, how do you choose the right technology stack for a project?
A: The right technology stack is all about finding an optimal balance between business needs and the current technical landscape. I would start with considering goals, whether it be cost optimization, performance, or scaling. I would analyze the current infrastructure, the volume of data, and data processing requirements in order to choose between AWS, Azure, and GCP, depending on which would offer the most appropriate tools. For instance, while working at Intelliswift with Apple’s AIML-Infrastructure team, I implemented data pipelines using Airflow and Snowflake. I chose them deliberately for their robustness in handling complex ETL processes and incremental data updates.
Q5: What role do certifications play in your professional development?
A: Certifications are a valuable way to stay updated and validate expertise. I hold certifications such as AWS Certified Solutions Architect and Business Transformation with Google Cloud, which have been instrumental in keeping me informed about new developments in cloud technologies. Beyond being credentials, they represent my commitment to continuous learning, which is essential in a field that evolves so rapidly.
Q6: Please elaborate on your experience in digital transformation projects
A: Digital transformation is more than just updating technology; it’s a strategic shift in how businesses operate. I have led several digital transformation projects, including the migration of legacy mainframe systems to cloud architecture. One notable project involved designing an OLTP and OLAP system on AWS Cloud for a major client. This project encompassed not only data migration but also data transformation to enhance analytics capabilities. The result was the implementation of a more agile and scalable system, enabling faster, data-driven decision-making for the business.
Q7: What do you find most rewarding about working as a Senior Technology Consultant?
A: The most rewarding aspect is seeing how my work impacts broader business strategies and helps unlock new opportunities. I am grateful to be part of projects where I can see tangible effects, particularly in fields like healthcare and insurance. The adoption of modern technology helps my clients address business challenges, stay competitive, and serve their customers more effectively.
Q8: How do you cope with problem-solving when put under immense pressure?
A: I rely on an analytical approach to navigate complex issues, breaking them down into smaller components, analyzing potential roadblocks, and developing multiple solutions. This method was essential in my role at Ford, where I led teams working on fleet management software for autonomous vehicles. With numerous touchpoints, any delay could impact the entire project timeline. I focused on establishing clear communication lines and following agile principles to ensure that each team member understood the project objectives and contributed effectively.
Q9: What do you see in the future for the role of a Data engineer?
A: Automation and intelligent systems of data will be the future of data engineering. The data volumes in the future just continue to explode, and the demand for self-optimizing pipelines, automated quality checks, and AI-driven insight into the management of that data will be increasingly in demand. I so believe in a future where machine learning will play an even more integral part in data operations to unleash insights dynamically more for the business. My objective is to contribute to building such intelligent data ecosystems capable of handling not only massive streams of data but also learning and adapting in real time.
Q10: Any advice for aspiring data professionals?
A: Stay curious and maintain a strong desire to learn; the field of data is constantly evolving. New tools and technologies emerge daily, so building a solid foundation in core concepts is essential, but don’t hesitate to explore new platforms and methodologies. Networking is equally important—connect with industry experts and contribute to open-source projects by providing continuous feedback. Most importantly, be patient; mastery takes time, but persistence and passion will go a long way.
Shanmukha Eeti’s career exemplifies the power of adaptability, continuous learning, and strategic thinking, transitioning from building traditional data warehouses to architecting modern cloud solutions. He continues to push the boundaries of what is possible in data engineering. His vision for the future includes developing smarter, self-sustaining data ecosystems that drive business transformation. His journey serves as an inspiration, showing that with dedication and a thirst for knowledge, there are no limits to what can be achieved.
First Published: 23 November, 2022
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