Apple • New York University • University of Alabama • University of Chicago • Delta Airlines • TicketMaster • Naca Logistics • Datascan Technologies • Bellsouth • Universal Weather and Aviation • Lithonia • Security One – S1 • Polaris Associates Inc
Krishna Reddy
Enterprise Data Architect & Digital Transformation Leader
Specializing in: Digital Transformation | Enterprise Architecture | Data Architecture | Cloud Solutions | ERP Implementation
Executive Summary
Accomplished Principal Architect with 24 years of expertise in data strategy, enterprise architecture, and delivering solutions that address critical business imperatives. Skilled in driving digital transformation, application modernization, cloud migration, and solution implementation through advanced technology and data engineering. Proven ability to achieve revenue growth, cost reduction, and risk mitigation. A trusted technical consultant who provides thought leadership, fosters stakeholder collaboration, and works closely with technical teams.
Professional Experience
Principal Data Architect – Mayo Clinic
Jun 2025 – Present
Led the design and delivery of a resilient, scalable data integration framework to continuously ingest data from Oracle Fusion into Snowflake, improving data availability, reliability, and enterprise decision-making.
Assessed underperforming data integration and reporting workflows and delivered actionable recommendations to improve performance, scalability, and overall reporting effectiveness.
Led evaluation and proof-of-concept initiatives for emerging Oracle AI capabilities, defining a strategic implementation roadmap to support phased adoption through 2026.
Directed a one-time migration of legacy data assets to the cloud, culminating in a successful transition to Snowflake and enabling the full retirement of the legacy data warehouse platform.
Evaluated vendors and software solutions, providing detailed cost models and recommendations aligned with budget constraints, architectural standards, and long-term enterprise strategy.
Accountable for improving the trustworthiness and reliability of enterprise data consumed across analytics platforms including Power BI, Looker, and ThoughtSpot, enabling confident, data-driven decision-making by business stakeholders.
Principal Data Architect | Data & AI Generalist – Americold
Oct 2024 – Jun 2025
Evaluated and optimized the post-SAP-to-Fusion architecture in the U.S., identifying gaps and implementing scalable improvements to support deployment across 36+ global entities.
Architected an enterprise integration framework to unify Oracle Fusion, operational data, and boundary system feeds within AWS, enabling a consistent and strategic enterprise data warehouse vision.
Oversaw database platforms and governed change management across a diverse data ecosystem including Oracle, Amazon DocumentDB, PostgreSQL, Redshift, DynamoDB, and MySQL; drove standardization, scalability, and performance across transactional, analytical, and NoSQL environments aligned with enterprise data governance and business goals.
As Principal Data Architect for the i3pl customer-facing platform, designed and deployed a near real-time enterprise data warehouse for 200+ facilities using a Medallion architecture. Integrated operational data from 10 distinct WMS platforms, financial data from Oracle Fusion, and additional boundary system feeds. Leveraged AWS services including S3, Glue, Lambda, Step Functions, and Redshift to build a scalable, modular pipeline supporting Bronze (raw), Silver (cleansed), and Gold (curated) layers for unified enterprise analytics and reporting.
Mentored and led data engineers across both onshore and offshore teams, providing technical guidance, architectural oversight, and best-practice implementation to deliver high-quality, scalable data solutions.
Principal Data Architect – Ticketmaster
Contract | Mar 2024 – Oct 2024
Led migration from SAP to Oracle Fusion as Principal Data Architect, providing thought leadership and shaping organization’s data strategy
Designed and implemented centralized data lakes and warehouses using Databricks for efficient processing and management of large-scale data
Established multi-tier architecture within Databricks: Bronze (raw), Silver (cleaned), Gold (business-ready) layers to enhance data quality and analytics performance
Implemented robust security measures including role-based access controls, data encryption, and proactive monitoring for data drift detection
Developed integration with Oracle CDM and TCA for master data management enabling sales transactions per contractual royalty agreements