Building Scalable Data Solutions: Insights from Santhosh Kumar Saminathan

Building Scalable Data Solutions: Insights from Santhosh Kumar Saminathan

Photo credit: Santhosh Kumar Saminathan

Santhosh Kumar Saminathan is a data engineering leader who has spent years creating systems to make sense of huge amounts of information. Over his 15-year career, he has worked on complex projects that help businesses make better decisions using data. As the Head of Data at Trepp Inc., a company specializing in commercial real estate and finance, he leads a team of 14 engineers. Together, they develop tools and systems to manage large datasets in areas like Collateralized Loan Obligations (CLOs) and Commercial Mortgage-Backed Securities (CMBS).

One of Santhosh’s standout projects at Trepp was designing an advanced data pipeline using Amazon Web Services (AWS). This pipeline processes financial data more efficiently, saving time and ensuring accurate information. He explains, “Building systems that can process billions of events daily is not just about the technology but about understanding the problem and breaking it into manageable parts.”

Before Trepp, Santhosh worked at BigCommerce, a popular e-commerce cloud platform. There, he built a real-time data system that handled more than 1.6 billion events daily, cutting processing time from 12 hours to just 5 seconds. This speed allowed BigCommerce to better serve its customers and improve its operations.

Leading Teams and Driving Innovation

Santhosh also guides teams to success. At Trepp, he introduced a new way of thinking about data called “Data-as-a-Product.” This approach encourages engineers to focus on how their work directly impacts the business, not just the technical side.

Santhosh believes strong teams are key to success. “Scaling data solutions is not just about the infrastructure, it is about building the right team and empowering them to think beyond the immediate problem,” he says. By creating a supportive work environment, he ensures his team has what they need to tackle challenges.

At BigCommerce, his leadership helped deliver tools integrated with platforms like Google Analytics and Meta, boosting customer engagement. These tools made it easier for businesses to use data, ultimately increasing revenue.

Trends in Data Engineering

Data engineering is growing rapidly as businesses depend more on real-time information. In 2025, global spending on data platforms is expected to exceed $122 billion. This is especially true in e-commerce, healthcare, and financial services, which rely on fast, accurate data to make decisions.

Santhosh’s work fits these trends right. At BigCommerce, he created systems powered by machine learning to recommend products to customers in real-time. This technology helped the company boost sales by 269 percent among users who interacted with product suggestions and increased overall revenue by 3.82 percent.

The systems he builds are also designed to last. For example, his CLO data pipeline at Trepp can adapt as business needs change, reducing the need for frequent updates or replacements.

Connecting Research with Real-World Applications

Santhosh also contributed to academic research. One of his papers on machine learning has been cited over 210 times, showing its influence on data engineering.

In addition to research, he has supported innovation through events like the Google-BigCommerce Hackathon. He helps inspire new ideas and highlight emerging talent in the tech industry by reviewing and mentoring during these events.

Balancing Technology and Responsibility

As industries pay more attention to sustainability and privacy, data engineering is evolving to meet these demands.

Santhosh’s work in GDPR and CCPA emphasizes fairness and transparency in data handling. With privacy regulations becoming stricter worldwide, creating systems that respect user rights is more important than ever. “The future of data engineering is about balancing innovation with responsibility,” he says.

Making Complex Systems Work for Everyone

Santhosh’s career shows how data systems can solve real business problems. Whether reducing delays in processing massive amounts of data or using machine learning to improve customer experience, his work highlights how data can be turned into actionable tools.

Santhosh is helping shape how businesses use data today and preparing them for the challenges of tomorrow by combining technical skills with effective leadership.