Platform Architect (Data Analytics & Management) - Vice President

We are seeking an experienced Platform Architect to provide end-to-end architectural leadership for the Client360 enterprise data platform. The role will own the technical integrity, scalability, security, resilience, and evolution of a cloud-based architecture spanning source integration, batch and near-real-time ingestion, Databricks Lakehouse processing, data governance, serving APIs, analytics, application integration, DevSecOps, and observability. The architect will translate business and non-functional requirements into executable designs, guide engineering teams through implementation, and ensure alignment with enterprise standards and regulatory controls. Architecture Scope: Enterprise and operational data source connections through APIs, JDBC sources, extracts, and event-driven streams. AWS-hosted data platform services, including VPC, Amazon S3, Glacier, IAM, Secrets Manager, and CloudWatch. Databricks Lakehouse architecture using Delta Lake, Databricks Medallion Architecture, Spark, Scala, SQL Warehouse, and governed catalog capabilities. Batch, near-real-time, pull-based, push-based, and event-driven integration patterns. Serving and integration layers using REST APIs, Java/Spring Boot services, Redis, MuleSoft etc. Engineering tools and platform operations using GitHub, Jenkins, JFrog Artifactory, Airflow, Grafana, Kibana, log analytics, and centralized authentication/SSO services. AWS infrastructure and storage architecture across VPC networking, S3, Glacier, IAM, Secrets Manager, key management, encryption, lifecycle and tiering policies, replication, backup, resiliency, performance, and cost management. Architecture documentation covering context, container, component, deployment, sequence, data-flow, threat, and operational views Integration/deployment of reusable AI capability/use cases into the platform. Key Responsibilities: Own and maintain the end-to-end solution architecture, reference models, integration patterns, technology standards, and architectural decision records. Convert business capabilities, data requirements, service-level objectives, security obligations, and regulatory constraints into scalable technical designs. Define target-state and transition architectures across ingestion, processing, storage, governance, orchestration, serving, APIs, applications, analytics, and archival, including data placement, partitioning, lifecycle, tiering, replication, backup, retention, encryption, and cost-optimization strategies. Evaluation/POCs on emerging tech for variety of functional use cases and technical scenarios. Establish patterns for batch and near-real-time ingestion using APIs, JDBC, file transfers, Auto Loader, and event-driven mechanisms.