About
Mr. Ravi Kumar is an accomplished and visionary technology leader with over 20 years of experience in Data Engineering, Cloud Architecture, Machine Learning, and Business Intelligence. With a strong foundation across multiple cloud platforms including AWS, Azure, and Google Cloud, his leadership has consistently delivered scalable, cost-efficient, and future-ready data solutions for large enterprises. He brings a proven track record of transforming complex legacy ecosystems into cloud-native data platforms, enabling businesses to achieve faster insights, improved performance, and enhanced governance.
As a Chief Technologist and Senior Cloud Architect, Mr. Kumar has spearheaded global cloud transformation initiatives by designing enterprise-wide data lake strategies, developing real-time analytics platforms, and implementing AI/ML-based predictive models using tools like SageMaker, Azure ML, and Google Vertex AI. His architectural vision has enabled organizations in sectors like insurance, financial services, retail, healthcare, and energy to unlock the true value of their data assets.
He has demonstrated expertise in data warehouse modernization and streaming architectures. Mr. Kumar has implemented petabyte-scale platforms using Snowflake, Redshift, BigQuery, and Azure Synapse and has integrated real-time data streams with technologies like Apache Kafka, Flink, Kinesis, and Spark. He has successfully transitioned traditional batch ETL systems into agile, real-time data pipelines using tools like AWS Glue, Apache Airflow, and Presto, drastically reducing data latency.
In addition to his technical depth, Mr. Kumar is a seasoned leader in DataOps and DevOps. He has operationalized CI/CD pipelines for data systems using Jenkins, GitLab, and Kubernetes, reducing deployment time and improving reliability. His expertise extends to data governance and self-service analytics using tools like Collibra, Informatica, Alation, Tableau, Power BI, and Looker.
Over the years, he has led critical projects at major organizations including Capital One, VISA, NIKE, and Catamaran, designing robust data architectures that ensure compliance with industry standards such as HIPAA, GDPR, PCI DSS, and SOX. From healthcare data governance portals to enterprise BI for retail operations, Mr. Kumar has architected platforms that deliver real-time insights, compliance, and operational excellence.
His leadership style fosters collaboration across global teams—Onsite, Offshore, and Nearshore—while mentoring teams in adopting Agile and Scrum methodologies for seamless delivery. His ability to align data strategy with business objectives has made him a trusted advisor to C-level stakeholders.
Mr. Ravi Kumar continues to explore the evolving frontiers of cloud-native analytics, MLOps, and federated data governance. His goal remains to empower organizations through intelligent, automated, and secure data platforms that scale with innovation.
Skills & Expertise
AWS
Tableau
Redshift
Power BI
Cognos
DataOps
Jenkins
Kubernetes
SSIS
SQL
PL/SQL
Oracle
DevOps
Azure
Apache Spark
Kinesis
GitLab
Kafka
Snowflake
Google Cloud
Presto
Informatica
Data Modeling
Looker
CI/CD
BigQuery
Apache Flink
Apache Airflow
Vertex AI
SageMaker
Real-Time Analytics
Data Governance
Data Governance
Alation
Alation
Azure ML
Collibra
DAX
ETL/ELT
Data Lake Architecture
MDM
HIPAA compliance
Data Warehousing
Business Intelligence (BI)
Research Interests
Cloud Data Architecture
AI/ML integration
Real-Time Data Processing
Streaming Analytics
Data Governance
Data Lake Solutions
Predictive Analytics
Business Intelligence
Healthcare & Pharma Data
Financial Compliance Platforms
Retail Data Systems
MLOps
Data Security & Compliance
Connect With Me
Experience
Senior Cloud Data Architect
Responsibilities:
• Spearhead the design and implementation of an enterprise-wide cloud-native data architecture using AWS Glue, Athena, PrestoDB, and other cutting-edge modern data technologies, driving a seamless transition to the cloud.
• Collaborate with senior leadership to provide strategic recommendations, delivering a flexible and scalable data platform architecture aligned with evolving business goals.
• Architect and enforce enterprise-wide standards and best practices for data integration, governance, and security through a robust framework that reduces risk and enhances data consistency.
• Develop sustainable and optimized data models supporting both real-time and batch processing, enabling comprehensive analytics for insurance policies, claims, and reinsurance data.
• Lead the modernization of data pipelines, transitioning from traditional ETL to serverless, scalable ELT architectures leveraging AWS Glue and Spark, ensuring faster, cost-effective data processing.
• Define and implement reusable design patterns for scalable data ingestion and transformation processes across multiple data sources, including CRM, Policy, and Claims systems.
• Implement advanced data governance frameworks and ensure compliance through tools like Collibra and Informatica, while providing oversight for the Architecture Review Board (ARB).
• Mentor and guide teams in modern ETL/ELT implementations using AWS Glue, ensuring adherence to modern data processing standards and cloud best practices.
• Conduct architectural assessments and audits of the current Enterprise Data Warehouse (EDW), driving continuous performance optimization and data pipeline enhancements.
• Oversee the integration of third-party vendor data and systems, including CRM and Reinsurance modules, into the enterprise cloud data platform, ensuring interoperability and seamless data flow.
• Lead cloud migration initiatives, leveraging serverless technologies like AWS Lambda, S3, and Redshift to modernize data storage, access, and analytics while driving significant reductions in operational costs.
• Streamline cross-functional collaboration between Onsite, Offshore, and Nearshore teams, ensuring delivery excellence across different geographic locations.
• Establish robust DataOps processes to automate data quality checks, data validation, and reconciliation, utilizing cutting-edge tools like Apache Airflow for orchestrating data workflows.
• Drive end-to-end project execution, from scope definition, estimation, and timeline management to successful delivery of high-impact, scalable solutions for the insurance sector.
• Continuously monitor and enhance data security, ensuring adherence to compliance regulations such as GDPR and HIPAA for sensitive insurance and claims data.
• Optimize the performance of complex queries and reporting layers, ensuring fast, efficient access to actionable insights for business users via Power BI and Tableau dashboards.
Cloud Data & BI Architect
• Developed an Architectural Framework for Financial Data Warehousing solutions with a focus on ensuring regulatory compliance, enhancing customer data management, and providing a unified data strategy.
• Spearheaded the design and implementation of a Cloud Data Warehouse integrating operational data stores, metadata repositories, and master data files, ensuring agile data governance and rapid scalability for financial reporting.
• Defined data management best practices tailored to financial data, enabling real-time analytics, risk management, and fraud detection.
• Led the rollout of Capital One’s Enterprise Data Warehouse (EDW), driving strategic initiatives for advanced business intelligence (BI) insights, enabling the Corporate Real Estate Group to make data-driven decisions.
• Developed strategies to comply with Basel III and Dodd-Frank regulations, ensuring that data architecture met stringent financial industry standards.
• Guided the cloud migration of on-premise data systems using AWS Glue, Redshift, and S3, aligning them with data sovereignty and privacy regulations like GDPR and CCPA.
• Implemented ETL pipelines leveraging Informatica, SSIS, and Control-M to optimize the performance of financial datasets, supporting predictive analytics, fraud detection, and loan risk assessment.
• Conducted architectural reviews for large-scale data integration projects, supporting real-time decision-making, data lineage tracking, and metadata management for better transparency and traceability in financial reporting.
• Technologies & Environment:
Oracle 10g, AWS Redshift, Informatica PowerCenter, SQL Server, SSIS, IBM DB2, SQL, PL/SQL, Control-M, Toad, Solaris, Windows XP.
Senior Data Architect-Healthcare & Pharmacy Solutions
• Acted as Senior Information Architect within the Healthcare & Pharmacy Data Governance Team, focusing on enhancing data access for self-service reporting and streamlining regulatory compliance within the pharmaceutical and healthcare domain.
• Led the Master Data Management (MDM) initiative to establish a Data Governance Portal, centralizing data ownership, glossary definitions, and access rights for secure and transparent handling of patient data.
• Collaborated with healthcare data stewards to develop data lineage, ensuring full traceability from source systems to pharmacy benefits reporting, enhancing accuracy in drug utilization and claims data.
• Drove the implementation of ETL best practices specific to healthcare, enabling data masking and anonymization to comply with HIPAA and HITECH regulations, ensuring patient privacy across data pipelines.
• Orchestrated the creation of a future state healthcare data landscape, optimizing operational data stores (ODS) and data warehouses for high-quality, integrated data, improving adjudication accuracy and claims processing for pharmacy benefit management.
• Established an Enterprise Data Model that supported pharmacy claims processing and real-time analytics, enabling the healthcare team to track medication adherence, cost patterns, and formulary compliance.
• Oversaw MDX-based reporting and data analysis for pharmaceutical claims, driving insights into prescription drug trends, cost containment strategies, and pharmacy performance metrics.
• Supported the development of data governance frameworks to monitor healthcare data quality, ensuring risk management and compliance with both FDA and CMS guidelines.
Technologies & Environment:
Oracle 9i, IBM WebSphere DataStage, Cognos 10.x, SQL Developer, Netezza, DB2, MDX, Putty, MS DOS, HIPAA-compliant Data Governance.
Senior Data Warehouse Architect
• Designed a strategic roadmap for data warehousing and BI initiatives, focusing on mastering data across global product lines, regional markets, and sales channels, enabling near-real-time data-driven decision-making for retail operations.
• Collaborated with business stakeholders and technical teams to gather and translate business requirements into technical solutions that drove global retail supply chain optimization and improved sales performance analytics.
• Architected and implemented a Kimball-style dimensional star-schema data warehouse model, supporting near-real-time reporting for critical retail metrics such as inventory turnover, sell-through rates, and product demand forecasting.
• Created comprehensive source-to-target mappings for ETL development, integrating operational data stores, CRM data, and market-level data to build a centralized data hub for global retail analysis.
• Leveraged Change Data Capture (CDC) and the Data Integration Hub to ensure synchronization of operational data stores and data marts, enabling real-time updates across various NIKE lines-of-business.
• Supported the development of Cognos BI reports for global and regional retail sales performance, facilitating end-to-end visibility into product lifecycles and marketing effectiveness.
• Designed and developed master data management (MDM) and data integration solutions, synchronizing data from customer relationship management (CRM) systems with multiple global applications to ensure data consistency for major product lines.
• Led the creation of business metadata repositories, mapping business terms, metrics, and related data to support retail sales, market analysis, and customer engagement efforts.
• Developed Cognos cubes for multi-dimensional analysis of global sales, enabling NIKE to track product performance by region, store, and customer segment.
• Provided architectural solutions to handle unbalanced hierarchies and optimize drill-down paths for global and regional sales analysis, improving retail demand forecasting accuracy.
Technologies & Environment:
Cognos 8.4, Tableau 7.x, SAP BI, Informatica 8.6, Erwin 7.x, Oracle 10g, SQL Server 2008, SSIS
ETL & BI Architect
• Architected a near-real-time financial data warehouse to integrate procurement, general ledger, and vendor payment data for improved financial reporting and spend analysis in the energy sector.
• Designed a tiered database structure, consisting of base tables (central data warehouse), dimensional models (star schema), and aggregate tables and cubes to optimize performance and flexibility for financial reporting and procurement analysis.
• Led a team of 7, focused on data architecture, data quality, metadata management, and ETL development, ensuring the data warehouse supported key financial operations, including cash flow analysis, cost control, and vendor management.
• Developed and optimized ETL processes using Informatica, incorporating real-time data integration and batch processing to ensure timely updates for procurement and general ledger data, supporting financial planning and analysis (FP&A).
• Facilitated focus group demos with business sponsors to gather feedback and refine data models based on evolving procurement and finance reporting needs.
• Worked closely with Cognos BI teams to design and test financial dashboards, enabling users to track purchase orders, invoice payments, and budget vs. actuals for capital projects.
• Provided data warehouse architecture expertise to the project team, advising on best practices for financial data integration, business intelligence, and metadata management within the energy sector.
• Supported the project management team in planning, estimating, and delivering additional phases of the data warehouse project, ensuring alignment with corporate financial reporting standards and SOX compliance.
• Engaged with business users to address any data warehouse issues and ensure the solution met regulatory requirements, including financial transparency and internal controls.
Technologies & Environment:
Oracle 11g, Informatica PowerCenter 8.1.1 SP3 / 8.6.1 SP5, Erwin, Visio, Java, Cognos
ETL & BI Architect
• Served as an enterprise-wide consultant, specializing in data analysis and data modeling for payment processing systems, driving the development of Enterprise Data Architecture (EDA) for transactional and customer data.
• Formulated a standardized methodology for data warehouse projects, guiding VISA’s payment data management efforts to support fraud detection, risk management, and customer behavior analytics.
• Promoted the use of data standards and reusable data models across the enterprise, supporting the integration of payment processing systems and ensuring compliance with PCI DSS standards.
• Led the development of a logical data model for VISA’s central data warehouse, focusing on the integration of payment transaction data with star-schema designs to enable robust reporting and real-time decision-making.
• Provided methodology, architecture, and transformation support for integrating data from source systems such as merchant accounts, customer credit card data, and transaction details, optimizing fraud detection systems.
• Participated in project planning and pilot scope sessions, delivering insights for payment system redesigns to enhance authorization and settlement processes.
• Assisted in the development of a repository to support enterprise data modeling efforts, including metadata management, ensuring full traceability and transparency for financial transactions.
• Developed physical database designs and ETL strategies for payment processing, ensuring data quality and alignment with regulatory requirements, including transaction integrity and data encryption for PCI compliance.
Technologies & Environment:
Informatica PowerCenter 7.x/8.x, Cognos Series 8, Report Net 1.1, Oracle 9i/10g, PL/SQL, Toad, Unix
Projects
Enterprise Data Architecture and Data Warehousing for Payment Systems
• Architected a near-real-time financial data warehouse to integrate procurement, general ledger, and vendor payment data for improved financial reporting and spend analysis in the energy sector.
• Designed a tiered database structure, consisting of base tables (central data warehouse), dimensional models (star schema), and aggregate tables and cubes to optimize performance and flexibility for financial reporting and procurement analysis.
• Led a team of 7, focused on data architecture, data quality, metadata management, and ETL development, ensuring the data warehouse supported key financial operations, including cash flow analysis, cost control, and vendor management.
• Developed and optimized ETL processes using Informatica, incorporating real-time data integration and batch processing to ensure timely updates for procurement and general ledger data, supporting financial planning and analysis (FP&A).
• Facilitated focus group demos with business sponsors to gather feedback and refine data models based on evolving procurement and finance reporting needs.
• Worked closely with Cognos BI teams to design and test financial dashboards, enabling users to track purchase orders, invoice payments, and budget vs. actuals for capital projects.
• Provided data warehouse architecture expertise to the project team, advising on best practices for financial data integration, business intelligence, and metadata management within the energy sector.
• Supported the project management team in planning, estimating, and delivering additional phases of the data warehouse project, ensuring alignment with corporate financial reporting standards and SOX compliance.
• Engaged with business users to address any data warehouse issues and ensure the solution met regulatory requirements, including financial transparency and internal controls.
Technologies & Environment:
Oracle 11g, Informatica PowerCenter 8.1.1 SP3 / 8.6.1 SP5, Erwin, Visio, Java, Cognos
Financial Data Warehouse for Procurement & General Ledger Integration
• Architected a near-real-time financial data warehouse to integrate procurement, general ledger, and vendor payment data for improved financial reporting and spend analysis in the energy sector.
• Designed a tiered database structure, consisting of base tables (central data warehouse), dimensional models (star schema), and aggregate tables and cubes to optimize performance and flexibility for financial reporting and procurement analysis.
• Led a team of 7, focused on data architecture, data quality, metadata management, and ETL development, ensuring the data warehouse supported key financial operations, including cash flow analysis, cost control, and vendor management.
• Developed and optimized ETL processes using Informatica, incorporating real-time data integration and batch processing to ensure timely updates for procurement and general ledger data, supporting financial planning and analysis (FP&A).
• Facilitated focus group demos with business sponsors to gather feedback and refine data models based on evolving procurement and finance reporting needs.
• Worked closely with Cognos BI teams to design and test financial dashboards, enabling users to track purchase orders, invoice payments, and budget vs. actuals for capital projects.
• Provided data warehouse architecture expertise to the project team, advising on best practices for financial data integration, business intelligence, and metadata management within the energy sector.
• Supported the project management team in planning, estimating, and delivering additional phases of the data warehouse project, ensuring alignment with corporate financial reporting standards and SOX compliance.
• Engaged with business users to address any data warehouse issues and ensure the solution met regulatory requirements, including financial transparency and internal controls.
Technologies & Environment:
Oracle 11g, Informatica PowerCenter 8.1.1 SP3 / 8.6.1 SP5, Erwin, Visio, Java, Cognos
Enterprise Data Warehousing & Business Intelligence (BI) Initiative for Retail Operations
• Designed a strategic roadmap for data warehousing and BI initiatives, focusing on mastering data across global product lines, regional markets, and sales channels, enabling near-real-time data-driven decision-making for retail operations.
• Collaborated with business stakeholders and technical teams to gather and translate business requirements into technical solutions that drove global retail supply chain optimization and improved sales performance analytics.
• Architected and implemented a Kimball-style dimensional star-schema data warehouse model, supporting near-real-time reporting for critical retail metrics such as inventory turnover, sell-through rates, and product demand forecasting.
• Created comprehensive source-to-target mappings for ETL development, integrating operational data stores, CRM data, and market-level data to build a centralized data hub for global retail analysis.
• Leveraged Change Data Capture (CDC) and the Data Integration Hub to ensure synchronization of operational data stores and data marts, enabling real-time updates across various NIKE lines-of-business.
• Supported the development of Cognos BI reports for global and regional retail sales performance, facilitating end-to-end visibility into product lifecycles and marketing effectiveness.
• Designed and developed master data management (MDM) and data integration solutions, synchronizing data from customer relationship management (CRM) systems with multiple global applications to ensure data consistency for major product lines.
• Led the creation of business metadata repositories, mapping business terms, metrics, and related data to support retail sales, market analysis, and customer engagement efforts.
• Developed Cognos cubes for multi-dimensional analysis of global sales, enabling NIKE to track product performance by region, store, and customer segment.
• Provided architectural solutions to handle unbalanced hierarchies and optimize drill-down paths for global and regional sales analysis, improving retail demand forecasting accuracy.
Technologies & Environment:
Cognos 8.4, Tableau 7.x, SAP BI, Informatica 8.6, Erwin 7.x, Oracle 10g, SQL Server 2008, SSIS
Pharmacy Benefit Management (PBM) Master Data Management (MDM) & Governance Portal
• Acted as Senior Information Architect within the Healthcare & Pharmacy Data Governance Team, focusing on enhancing data access for self-service reporting and streamlining regulatory compliance within the pharmaceutical and healthcare domain.
• Led the Master Data Management (MDM) initiative to establish a Data Governance Portal, centralizing data ownership, glossary definitions, and access rights for secure and transparent handling of patient data.
• Collaborated with healthcare data stewards to develop data lineage, ensuring full traceability from source systems to pharmacy benefits reporting, enhancing accuracy in drug utilization and claims data.
• Drove the implementation of ETL best practices specific to healthcare, enabling data masking and anonymization to comply with HIPAA and HITECH regulations, ensuring patient privacy across data pipelines.
• Orchestrated the creation of a future state healthcare data landscape, optimizing operational data stores (ODS) and data warehouses for high-quality, integrated data, improving adjudication accuracy and claims processing for pharmacy benefit management.
• Established an Enterprise Data Model that supported pharmacy claims processing and real-time analytics, enabling the healthcare team to track medication adherence, cost patterns, and formulary compliance.
• Oversaw MDX-based reporting and data analysis for pharmaceutical claims, driving insights into prescription drug trends, cost containment strategies, and pharmacy performance metrics.
• Supported the development of data governance frameworks to monitor healthcare data quality, ensuring risk management and compliance with both FDA and CMS guidelines.
Technologies & Environment:
Oracle 9i, IBM WebSphere DataStage, Cognos 10.x, SQL Developer, Netezza, DB2, MDX, Putty, MS DOS, HIPAA-compliant Data Governance.
Cloud-Based Real-Time Data Integration for Financial Services
• Developed an Architectural Framework for Financial Data Warehousing solutions with a focus on ensuring regulatory compliance, enhancing customer data management, and providing a unified data strategy.
• Spearheaded the design and implementation of a Cloud Data Warehouse integrating operational data stores, metadata repositories, and master data files, ensuring agile data governance and rapid scalability for financial reporting.
• Defined data management best practices tailored to financial data, enabling real-time analytics, risk management, and fraud detection.
• Led the rollout of Capital One’s Enterprise Data Warehouse (EDW), driving strategic initiatives for advanced business intelligence (BI) insights, enabling the Corporate Real Estate Group to make data-driven decisions.
• Developed strategies to comply with Basel III and Dodd-Frank regulations, ensuring that data architecture met stringent financial industry standards.
• Guided the cloud migration of on-premise data systems using AWS Glue, Redshift, and S3, aligning them with data sovereignty and privacy regulations like GDPR and CCPA.
• Implemented ETL pipelines leveraging Informatica, SSIS, and Control-M to optimize the performance of financial datasets, supporting predictive analytics, fraud detection, and loan risk assessment.
• Conducted architectural reviews for large-scale data integration projects, supporting real-time decision-making, data lineage tracking, and metadata management for better transparency and traceability in financial reporting.
• Technologies & Environment:
Oracle 10g, AWS Redshift, Informatica PowerCenter, SQL Server, SSIS, IBM DB2, SQL, PL/SQL, Control-M, Toad, Solaris, Windows XP.
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