Raveendra Babu Darsi

Principal / Enterprise Architect with 24+ years leading enterprise architecture, cloud-native platforms, and large-scale integration across financial services, supply chain, and commerce-adjacent domains. Drives target-state architecture, technology roadmaps, blueprints, and architecture governance under CTO/EA organizations, translating business strategy into modernized, scalable technology landscapes and serving as an enterprise change agent. Designs cloud-native, event-driven, and serverless architectures on AWS and GCP — microservices, API-led connectivity, and real-time signal processing (Kafka, Kinesis, GCP Pub/Sub, Lambda, EventBridge) — that power responsive, personalized, and context-aware experiences across digital and operational touchpoints.

Builds enterprise data foundations for personalization and decisioning — canonical Customer/Party master data (MDM/CDP-style modeling with match–merge–survivorship), S3/Redshift data lakes, and streaming pipelines — and integrates AI/ML and GenAI (RAG, embeddings, vector stores, LLM-assisted workflows) into data and application landscapes. Applies enterprise-architecture and modeling methodologies (EA, MDA, NIEM, IAA) and API-first / composable principles; leads architecture reviews and governance for AI-based and connected initiatives; and partners with product, engineering, and data-science teams to scale AI/ML use cases with IaC (Terraform, CloudFormation) and CI/CD. Accomplished communicator and storyteller of complex AI- and cloud-driven business value, balancing near-term delivery with long-term architecture vision and driving clarity and structure in ambiguous, fast-moving environments.

Enterprise Integration & Data Platform Architect – Dealer Financial Services Modernization at Honda (2025-08 – Present)

• Architected enterprise-grade AWS infrastructure aligned with security, networking, and governance standards - VPC networking, IAM least-privilege, compute (Lambda/Glue), S3 storage, Aurora PostgreSQL and Redshift databases, and CloudWatch monitoring - provisioned via Terraform/CloudFormation Infrastructure-as-Code and CI/CD for repeatable, secure deployments.
• Developed the target-state architecture, phased modernization roadmap, and cloud adoption plan, translating technical tradeoffs into executive options analyses and decision matrices and aligning to enterprise architecture standards and operational readiness.
• Defined the data architecture and platform strategy for Honda's enterprise DataHub on AWS — spanning the S3 data lake, Glue ETL pipelines, Redshift warehouse, and Aurora PostgreSQL master data store — modernizing 42-year-old mainframe (DB2/VSAM) data flows into a cloud-native platform optimized for performance, reliability, cost, and scalability.
• Built and optimized scalable batch and real-time (streaming) data pipelines using AWS Glue, Kinesis, Lambda, SQS/SNS, and event-driven patterns, ingesting and orchestrating data across 70+ source interfaces (DataScan WI, CASS, PRISM, Salesforce, Oracle PeopleSoft GL, OneTrust) with seamless cutover from legacy WebSphere MQ/mainframe integration.
• Architected the enterprise Process Integration Map and interface specifications for the 70+ DataHub interfaces - including the Oracle PeopleSoft GL financial-posting integration and OEM inventory flows - standardizing reusable API-led, event-driven, and file/SFTP integration patterns, canonical mappings, naming/scheduling conventions, and error-handling standards, and re-platforming legacy WebSphere MQ/mainframe file-based interfaces to real-time APIs.
• Designed the canonical Customer/Party master data model (11 entities) and a tiered match–merge–survivorship framework using AWS Entity Resolution (ML-based matching) and dbt transformations on Redshift, establishing golden-record data quality and stewardship workflows across millions of customer records.
• Defined and enforced data governance, quality, and compliance frameworks across the platform — including CCPA/GPC privacy opt-out propagation, OneTrust consent integration, field-level data lineage and gap analysis between source systems and the canonical model, and SOX risk controls.
• Designed and implemented data contracts and event flows in collaboration with backend, platform, and security engineering teams — defining interface specifications, schema standards, and canonical mappings across DataScan WI, legacy mainframe, OEM, auction partner, and AWS analytics platforms using API-led, event-driven, and secure file-based patterns.
• Built monitoring, logging, and alerting for data pipelines and services (CloudWatch, SNS) and contributed to CI/CD workflows for data deployment and automation using Terraform, CloudFormation, and infrastructure-as-code standards for repeatable platform provisioning.
• Owned the end-to-end delivery lifecycle across the 70+ DataHub interfaces - requirements analysis, solution design, technical specification and 4-eye design reviews, build oversight, integration/regression testing, cutover, hypercare, and production support - including daily batch/interface health monitoring, incident triage, P1/P2 escalation, and root-cause and corrective-action resolution for Finance-critical data flows (GL, AR, AP, and dealer financial services).
• Led onshore/offshore delivery teams and managed-service/SI partners across the program - directing daily handoffs, priority setting, ServiceNow change/incident/problem management, and deployment sign-offs; reviewed and challenged vendor estimates, timelines, and solution options, and produced cutover runbooks, support playbooks, and executive-ready status, risk, issue, and dependency reporting for leadership.
• Drove data platform modernization initiatives — including a two-phase migration strategy for 546K+ historical reports (~17TB) and migration of file-based processes to real-time APIs — partnering with leadership to translate technical tradeoffs into options analyses and decision matrices.