Data and AI strategy
Shape governed data architecture, analytics foundations, and applied AI/ML programs that connect executive priorities with reliable decision platforms.
Technology executive | Data, AI, product, and platform strategy
Building trusted data, AI, and analytics platforms at enterprise scale.
Senior enterprise data, visualization, and platform engineering leader with 20+ years across cloud architecture, BI ecosystems, governance, and responsible AI/ML delivery.
Shuvro brings more than 20 years of progressive leadership across software engineering, data engineering, data management, governance, visualization, cloud architecture, and AI/ML solutions delivery.
His work spans global retail, e-commerce, healthcare, finance, analytics, marketing, supply chain, merchandising, membership, and digital experience functions, with a record of scaling governed platforms that serve tens of thousands of users.
Professional profile
Mission-driven leadership across data, AI, product, and transformation.
Shuvro leads enterprise data and visualization platform strategy, bringing governed data, cloud-native architecture, analytics, and AI/ML delivery into operating models that large organizations can trust and scale.
His work sits at the intersection of platform engineering, executive advisory, product thinking, and responsible data governance across regulated, high-scale environments.
He translates complex technical systems into clear choices for technical and non-technical stakeholders, coaching teams while aligning delivery, user adoption, compliance, and business outcomes.
What he helps organizations do
Build systems that make better decisions possible.
Product innovation
Guide platform and product teams from strategy through delivery with modern CX, agile execution, and measurable adoption outcomes.
Cloud-native platforms
Build reliable, secure technology foundations across cloud, software engineering, DevOps, BI, and enterprise data platforms.
Organizational transformation
Coach teams, translate complex technical concepts, and help leaders align people, process, governance, equity, and technology around a shared mission.
Enterprise impact
Credibility built through scale, resilience, and measurable outcomes.
Analytics users enabled
Directed enterprise strategy and deployment for a unified Data & Visualization Platform ecosystem spanning Databricks, Snowflake, Power BI, Tableau, Looker, and Qlik while managing a $30M+ annual platform budget.
Vulnerabilities remediated
Strengthened enterprise-grade security, compliance, and risk posture while completing hundreds of audits across complex analytics and data platforms.
Global platform team leadership
Led distributed engineering teams delivering cloud data lakehouse, BI, ELT, ML, and governed data capabilities across Azure and GCP.
Platform uptime achieved
Built resilient cloud-native platforms and operating models for high-availability analytics, reporting, and machine learning workflows.
Annual infrastructure savings
Optimized data storage and cleanup policies, reducing infrastructure costs by 25% while improving platform performance and governance.
Cloud-native adoption scaled
Architected a public cloud consumption model and HA/DR strategy that reduced downtime risk and improved deployment speed.
ETL/ELT pipelines supported
Provided enterprise-scale data pipeline foundations across Databricks, BigQuery, BigLake, Airflow, Azure, and GCP for analytics and ML workflows.
Provisioning lead time reduced
Spearheaded private cloud messaging services and PaaS patterns that dramatically accelerated infrastructure deployment for critical applications.
Monthly finance events processed
Built a finance integration layer synchronizing cross-border data across global platforms, improving reliability and reporting accuracy.
Databricks
Snowflake
Power BI
Tableau
Looker
Qlik
Azure
GCP
Kafka
Alation
TrustLogix
Operating strengths
Technical depth with executive clarity.
Responsible governance
Data practices that improve confidence, lineage, compliance, privacy, and long-term trust.
Human-centered design
Solutions shaped around real users, clear workflows, and inclusive outcomes.
Cross-functional leadership
Teams that work across technical, product, operational, and executive boundaries.
Stakeholder translation
Complex systems explained clearly for technical and non-technical stakeholders.
Enterprise delivery
Experience across diverse industries, enterprise environments, and modern delivery teams.
Platform economics
Budget, vendor, performance, and cost optimization across complex data ecosystems.
Regulated data environments
Governance and compliance experience across SOX, CCPA, CPRA, GDPR, and MHMD contexts.
Leadership record
Enterprise platform leadership across healthcare, retail, e-commerce, and software.
McKesson | Senior Director, Data & Visualization Platform Engineering
- Defines enterprise-wide Data & Visualization Platform strategy across Databricks, Snowflake, Power BI, Tableau, Looker, Qlik, Alation, TrustLogix, DataStage, Kafka, and CDC.
- Scales governed self-service analytics, platform performance, cost optimization, AIM28, and advanced analytics.
- Strengthens high-availability data products across Finance, BSMR, Gx, Customer Operations, and Distributed Experiences.
McKesson | Director, Data & Visualization Platform Engineering
- Led unified BI and data architecture across Power BI, Looker, Tableau, Databricks, Snowflake, DataStage, Kafka, and CDC.
- Established analytics governance and catalog strategy with Alation and TrustLogix.
- Remediated 12K+ vulnerabilities and completed hundreds of audits while improving trusted data storytelling.
Walmart Global Tech | Senior Engineering Manager II, Big Data & ML Platforms
- Directed cloud data lakehouse and multi-cloud platform strategy across Databricks, BigQuery, BigLake, Azure, GCP, Power BI, and Looker.
- Led 55 engineers across ELT, governance, privacy compliance, and machine learning platform capabilities.
- Improved production stability with disciplined code review, testing, release management, and 90%+ repository test coverage.
Sam's Club | Principal Cloud Platform Architect, Public Cloud Infrastructure
- Designed scalable public cloud infrastructure and HA/DR architecture for a 300-engineer organization.
- Improved deployment speed and operational resilience through cloud-native development practices.
Walmart Labs | Principal Cloud Platform Architect, Data Foundation
- Led private cloud data solutions across messaging, Kafka, Storm, Elastic, Cassandra, and database platforms.
- Reduced deployment timelines and improved service availability for enterprise teams.
Walmart eCommerce and Walmart | Enterprise Architecture and Finance Data Integration
- Advanced SOA strategy and large-scale application and data architecture.
- Built finance integration systems processing 100M+ monthly events across global platforms.
Microsoft, Thomson Reuters, OATI, and Minnesota State University
- Built software, data retrieval, web, and embedded platform capabilities.
- Delivered Networked Multimedia features for Windows Embedded Compact OS.
PhD
Information Systems, Data Analytics & Decision Support, Dakota State University
MBA
Webster University
MS & BS
Computer Science, Minnesota State University, Mankato
Working principles
Practical innovation, grounded in trust.
Make strategy executable
Good strategy has to survive contact with delivery. Shuvro focuses on turning vision into operating models, roadmaps, and teams that can execute.
Design for adoption
Technology succeeds when people understand it, use it, and trust it. Clear CX, inclusive practices, clear communication, and clear ownership matter.
Use data responsibly
Better decisions depend on reliable data, strong governance, and a thoughtful approach to AI that respects impact, risk, and equity.
Advisory, speaking, and executive support
Focused help for leaders modernizing data, AI, governance, and platform operating models.
Data and AI platform advisory
Guidance on governed architecture, BI ecosystems, AI/ML delivery models, platform investment, and executive alignment.
Cloud, analytics, and operating model reviews
Practical review of cloud data foundations, analytics platforms, ownership models, governance gaps, adoption patterns, and cost posture.
Responsible AI and governed analytics talks
Executive and practitioner perspective on data quality, lineage, privacy, ethical AI, stakeholder trust, and human-centered adoption.
Team coaching and executive translation
Coaching for distributed engineering, product, and platform teams responsible for secure delivery, reliability, and measurable outcomes.
Best-fit conversations
Reach out for data and AI strategy, platform modernization, governance reviews, executive advisory, teaching, conference talks, or leadership conversations around trusted analytics at scale.
Executive perspectives
Practical perspectives on building trusted data, AI, and analytics platforms at enterprise scale.
Responsible AI governance starts before model selection
Effective AI programs define ownership, data quality, risk review, explainability, and human oversight before teams standardize on models, vendors, or delivery tooling.
Explore perspectiveGoverned self-service analytics should accelerate trust
Strong BI ecosystems reduce friction by making certified data, lineage, ownership, and reusable patterns easier to find without slowing down high-confidence decisions.
View related impactPlatform operating models turn engineering into enterprise value
Durable platforms connect technical architecture with adoption, reliability, cost discipline, security posture, and executive clarity about tradeoffs.
Review experienceResearch and professional presence
Research, patents, and professional service.
Publications 9 entries
- 2025: An Exploration of the Ethical Challenges in Artificial Intelligence Research, Handbook on Information Systems and Society, 2025.
- 2023: Fairness Challenges in Artificial Intelligence, Chakrobartty, Shuvro, and El-Gayar, Omar, Encyclopedia of Data Science and Machine Learning, 2023.
- 2022: Towards a Performance-explainability-fairness Framework for Benchmarking ML Models, Chakrobartty, Shuvro, and El-Gayar, Omar, The Americas Conference on Information Systems, 2022.
- 2021: Explainable Artificial Intelligence in the Medical Domain: A Systematic Review, Chakrobartty, Shuvro, and El-Gayar, Omar, The Americas Conference on Information Systems, 2021.
- 2005: On Concatenative Magic Squares, Chakrobartty, Shuvro, 2005.
- 2004: Significance Testing in Exact Logistic Multiple Regression, Rahman, Mezbahur, and Chakrobartty, Shuvro, Bulletin of the Malaysian Mathematical Sciences Society, 2004.
- 2004: Tests for uniformity: a comparative study, Rahman, Mezbahur, and Chakrobartty, Shuvro, Journal of the Korean Data and Information Science Society, 2004.
- 2004: A framework for a Bangla concatenative text-to-speech synthesis system, Syed, Mahbubur R, Chakrobartty, Shuvro, and Bignall, Robert James, Information Resources Management Association International Conference, 2004.
- 2004: Study of Speech Synthesis Systems Towards Implementation of a Multilingual Text-To-Speech System, Chakrobartty, Shuvro, 2004.
Patents 19 entries
- 2024: Location based register rules, Chakrobartty, Shuvro, Sherrill, Edward, Danda, Gopi Kishore, Michaelsamy, Britto, Rajendran, Prasanna, and Humphrey, John Michael, U.S. Patent 12147959.
- 2024: Apparatus and method of monitoring product placement within a shopping facility, U.S. Patent 12123155.
- 2024: Shopping facility assistance systems, devices and methods, Michael D. Atchley, Donald R. High, Chakrobartty, Shuvro, Kay, Karl, McHale, Brian G., Taylor, Robert C., Thompson, John P., Welch, Eric E., and Winkle, David C., U.S. Patent 12084824.
- 2023: Apparatus and method of monitoring product placement within a shopping facility, High, Donald, Chakrobartty, Shuvro, and Taylor, Robert, U.S. Patent 11761160.
- 2023: Location Based Register Rules, Chakrobartty, Shuvro, Sherrill, Ted, Danda, Gopi Kishore, Michaelsamy, Britto, Rajendran, Prasanna, and Humphrey, John Michael, U.S. Patent 11710113.
- 2023: Shopping facility assistance systems, devices and methods, High, Donald, Atchley, Michael, Chakrobartty, Shuvro, Kay, Karl, McHale, Brian, Taylor, Robert, Thompson, John, Welch, Eric, and Winkle, David, U.S. Patent 11679969.
- 2022: Systems and methods for promotional programs, Chakrobartty, Shuvro, Jay, NAIR, NAIR, Sandya, Meyer, Sara, Alex, HURD, Hodges, Marina, Sherrill, Ted, Solis, Saul, Mandava, Hanumantha, Danda, Gopi, Venable, Chris, and Hunter, Samuel, U.S. Patent 11238484.
- 2021: Shopping facility assistance systems, devices and methods, High, Donald, Atchley, Michael, Chakrobartty, Shuvro, Kay, Karl, McHale, Brian, Taylor, Robert, Thompson, John, Welch, Eric, and Winkle, David, U.S. Patent 11046562.
- 2021: Apparatus and method of monitoring product placement within a shopping facility, High, Donald, Chakrobartty, Shuvro, and Taylor, Robert, U.S. Patent 11034563.
- 2021: Systems and methods for promotional programs, Chakrobartty, Shuvro, Jay, NAIR, NAIR, Sandya, Meyer, Sara, Alex, HURD, Hodges, Marina, Sherrill, Ted, Solis, Saul, Mandava, Hanumantha, Danda, Gopi, Venable, Chris, and Hunter, Samuel, U.S. Patent 10902454.
- 2020: Apparatus and method of monitoring product placement within a shopping facility, High, Donald, Chakrobartty, Shuvro, and Taylor, Robert, U.S. Patent 10633231.
- 2019: Sensor data analytics and alarm management, Chakrobartty, Shuvro, Michaelsamy, Britto, Muniyan, Kalaiselvan, Sayers, David, and Duncan, Auer, U.S. Patent 10498585.
- 2019: Trash can monitoring systems and methods, High, Donald, Chakrobartty, Shuvro, Winkle, David, and Atchley, Michael, U.S. Patent 10486951.
- 2019: Systems, devices and methods of controlling motorized transport units in fulfilling product orders, High, Donald, Chakrobartty, Shuvro, Winkle, David, and Taylor, Robert, U.S. Patent 10351399.
- 2019: Shopping facility assistance systems, devices and methods, High, Donald, Atchley, Michael, Chakrobartty, Shuvro, Kay, Karl, McHale, Brian, Taylor, Robert, Thompson, John, Welch, Eric, and Winkle, David, U.S. Patent 10280054.
- 2019: Shopping facility assistance system and method having a motorized transport unit that selectively leads or follows a user within a shopping facility, McHale, Brian, Winkle, David, Atchley, Michael, Chakrobartty, Shuvro, and High, Donald, U.S. Patent 10239740.
- 2019: Apparatus and method of monitoring product placement within a shopping facility, High, Donald, Chakrobartty, Shuvro, and Taylor, Robert, U.S. Patent 10239738.
- 2019: Systems, devices and methods for restoring shopping space conditions, High, Donald, Chakrobartty, Shuvro, Taylor, Robert, and McHale, Brian, U.S. Patent 10189692.
- 2018: Systems, devices and methods of controlling motorized transport units in fulfilling product orders, High, Donald, Chakrobartty, Shuvro, Winkle, David, and Taylor, Robert, U.S. Patent 9896315.
Teaching
Adjunct Professor at the University of Texas at Arlington, teaching graduate-level Data Warehouse & Business Intelligence and Data Engineering courses that connect foundational data management with modern data engineering practice.
Reviewer
Peer reviewer for HICSS, AMCIS, Decision Sciences Institute, the Research Handbook on Information Systems and Society, and the Encyclopedia of Data Science and Machine Learning.
Digital presence
For direct conversation, a private message on LinkedIn is the best way to quickly reach Shuvro.
Connect
Start a focused conversation about data, AI, governance, or platform leadership.
For advisory, speaking, teaching, platform strategy, governed analytics, responsible AI, or executive technology leadership conversations, a private message on LinkedIn is the best way to quickly reach Shuvro.