Shankar Das Boddu

Shankar Das Boddu has built a distinguished career in enterprise data engineering by operating at the convergence of cloud-native analytics, large-scale data platforms, and machine learning infrastructure. Over 15 years, he has developed a professional record defined by technical depth, architectural leadership, and the consistent modernization of enterprise analytics ecosystems across healthcare, technology, finance, telecommunications, and education. His work reflects the profile of an engineer who does not merely build pipelines, but architects the data foundations that allow institutions to make faster, more reliable, and more intelligent decisions at scale.

In his current role as Senior Technical Lead at HCL America Inc., supporting Children’s Hospitals Minnesota, Shankar is helping modernize an enterprise analytics and data platform in a healthcare setting where the quality, accessibility, and timeliness of data have direct operational significance. He has led the migration of a Yellowbrick data warehouse into an Azure Fabric-based hybrid cloud environment that integrates diverse clinical and operational datasets into a unified healthcare platform. His contribution stands out not only for its technical ambition, but for its problem-solving rigor: leadership recognized him for solving challenges that more than 30 engineers had previously attempted without success. He also engineered a custom Python-based pipeline that extracts remittance advice data from Department of Health PDF documents using OCR and data transformation libraries, converting difficult, unstructured source material into structured datasets that support analytics and clinical decision-making. This kind of work demonstrates a rare combination of engineering precision, applied innovation, and measurable enterprise utility.

Before this, while supporting Microsoft through HCL America, Shankar led a team of nine engineers responsible for delivering scalable data pipelines for the FastTrack Business Intelligence Platform. There, he architected secure financial data pipelines using Azure Data Factory, Synapse Analytics, Databricks, and Microsoft Fabric components, ensuring that Tier-1 global customers could be supported while maintaining compliance with EU and broader global data localization requirements. His leadership in distributed processing and PySpark optimization enabled the platform to handle demanding financial analytics workloads while preserving strict security and compliance standards. This work placed him at the center of a mission-critical data environment where governance, performance, and resilience were all non-negotiable.

A major chapter of his career unfolded during his support of Google LLC, where he worked on enterprise data engineering initiatives inside the Corporate Data and Analytics ecosystem supporting Google’s global financial systems. In that setting, he architected scalable pipelines that migrated financial data from enterprise systems such as Oracle EBS and SAP into Google Cloud platforms including BigQuery and Colossus. He also designed multi-layered enterprise data architecture, created data freshness reporting to meet SLA requirements, developed rules-based data quality frameworks, and implemented metadata-driven validation systems that improved production stability and strengthened governance at enterprise scale. This body of work underscores his ability to deliver both foundational architecture and operational excellence in highly complex corporate environments.

His earlier work in healthcare data modernization at Fresenius Medical Care North America further highlights his strength in building high-impact analytics environments. As Principal Software Engineer, he led the architecture of a clinical data lake and supported migration from on-premise systems to AWS cloud infrastructure. He introduced medallion architecture principles, transformed legacy ETL processes into PySpark pipelines orchestrated through AWS Glue, and automated metadata-driven Informatica pipeline code generation using Python. The impact was not only technical but organizational: the trust earned through his team’s execution contributed to an expansion of team size from two to fourteen in a short span, a practical indicator of stakeholder confidence in both the architecture and the leadership behind it.

Across additional engagements for Ruffalo Noel Levitz, Health Care Service Corporation, Nextsource, Microsoft, and Cox Communications, Shankar consistently delivered systems that improved data access, performance, reporting security, and enterprise visibility. His work has included Tableau dashboard architectures, Azure cloud data warehouse migration, real-time workforce analytics, automated business reporting for multi-billion-dollar sales operations, and ETL optimization for telecommunications analytics platforms. Particularly notable is the recognition he received while supporting Microsoft earlier in his career, where his contributions were described as exceptional by senior executives and regarded as a new benchmark within his practice area. Such recognition suggests not only technical competence, but a sustained level of professional excellence that sets him apart from peers.

What emerges from this record is a portrait of a technologist whose contributions span architecture, execution, leadership, and mentorship. Shankar Das Boddu has repeatedly worked in environments where data engineering is central to enterprise performance, regulatory compliance, and strategic decision-making. His projects show breadth across industries, mastery across major cloud ecosystems, and a consistent pattern of converting complexity into scalable, governed, and business-enabling systems. That combination makes him a strong and credible candidate for distinction at the Fellowship level.