In the current era of digital transformations, where cloud computing dominates conversations, Srinivasa Kalyan Vangibhurathachhi is taking the hybrid route, bridging the best of both worlds through hybrid data architectures.
Kalyan’s work spans several industries, especially in highly regulated, high-volume sectors like telecom and healthcare. His approach is rooted in balance: ensuring enterprises don’t blindly migrate everything to the cloud but instead make smart, deliberate transitions that combine on-premises strengths with cloud agility.
One of Kalyan’s notable achievements has been leading the migration of critical Oracle and IBM DataStage workloads into Snowflake and Azure environments. In doing so, he helped businesses reduce infrastructure costs from $44 million to $32 million, a 27% reduction by retiring redundant servers and using elastic cloud resources only when needed.
System scalability, a persistent challenge for legacy infrastructure, saw a sharp 138% improvement. By integrating Snowflake’s burst-on-demand model with on-prem parallel processing capabilities, his team redefined what responsiveness means in large data systems. At the same time, processing times for complex data jobs dropped by 38%, and engineering productivity increased by 30%, thanks to the use of standardized ETL and ingestion templates.
His influence extends beyond cost savings. At a Tier-1 U.S. telecom provider, Kalyan orchestrated a zero-downtime migration of Oracle workloads using a combination of Snowpipe for streaming data and parallel processing with DataStage. That project demonstrated how cloud and on-prem environments can coexist, each doing what it does best.
In another project for a financial services client, Kalyan helped design a hybrid ETL framework that ran across AWS and Azure while ensuring that sensitive data never left on-premises systems. By using Snowflake connectors and orchestrating secure data movement between platforms, the firm could meet regulatory obligations without compromising on scalability.
He’s also delivered hybrid analytics capabilities. By combining Snowflake’s Streams and scheduled Tasks with real-time transactional data from on-prem systems, Kalyan helped build responsive dashboards that power business decisions across distributed environments.
Measurable outcomes from his work include a 35% drop in infrastructure costs post-migration, a 60% faster post-architecture redesign, a 50% increase with the cloud burst-on-demand model and a 40% boost in engineering productivity. More impressively, these changes came with near-zero downtime.
To come upon the desired outcomes, he had to stumble upon certain considerations. In one instance, moving data securely in real time between cloud and on-prem systems had to comply with stringent regulatory guidelines. Kalyan solved this by designing encryption-based staging pipelines and improving hybrid orchestration with Snowflake and DataStage. He also tackled data consistency using Snowflake’s Time Travel and Zero-Copy Cloning features, ensuring that nothing was lost or corrupted mid-migration.
Another issue was the fragmentation between on-prem and cloud teams, both using different tools and workflows. Kalyan addressed this by standardizing pipelines, implementing version-controlled libraries, and role-based platform access, enabling seamless collaboration.
Reflecting on his experience, Kalyan believes that hybrid systems are not temporary solutions. “Hybrid is not a compromise but a strategy,” he explains. “Resilient enterprises treat hybrid architecture as an innovation enabler, not just a stepping stone to full-cloud.”
Speaking of hybrid systems, he also adds the successful factors of a hybrid system, like data mobility, metadata governance and cross-platform observability, alongside speed and cost.
He sees a trend in what he calls “Data Gravity Zones,” where compute and storage follow the flow of usage, dynamically shifting between cloud, edge, and on-premise based on data access patterns. In this context, Kalyan emphasizes the importance of building systems that prioritize interoperability. That means leaning on open standards like Parquet and JSON, embracing open APIs, and avoiding vendor lock-in by default.
Kalyan continues to build frameworks that help organizations move according to situations. His work suggests that the real innovation in data infrastructure isn’t in abandoning legacy, it’s in making things work together for smoothness.