Databricks Architect (Onsite Hybrid)

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are currently seeking a Databricks Architect (Onsite Hybrid) to join our team in Atlanta, Georgia (US-GA), United States (US). We are seeking a highly experienced Databricks Architect / Primary Architect – Databricks Lakehouse & Data Governance to lead the architecture, governance, security, and modernization of enterprise data platforms on Databricks. The role will serve as the architectural authority for Databricks initiatives from requirement intake and solution design through implementation and production support, partnering with business stakeholders, data owners, governance bodies, security, application teams, data engineering teams, source-system SMEs, vendors, and leadership. Job Responsibilities Include: Lead enterprise Databricks Lakehouse architecture using Medallion Architecture (Bronze, Silver, Gold), establishing scalable, reusable, secure, and governed platform patterns. Define the target-state Databricks architecture across ingestion, transformation, storage, orchestration, analytics, streaming, data sharing, and consumption layers. Design and govern Delta Lake / Delta-based data architectures, including data layout, performance optimization, schema evolution, data lifecycle, and workload-management standards. Own the enterprise data-governance architecture on Databricks, with strong focus on Unity Catalog for centralized cataloging, access control, data discovery, lineage, ownership, and governed data sharing. Define data domains, catalogs, schemas, ownership models, classification standards, business metadata, technical metadata, and stewardship patterns in partnership with enterprise data-governance teams. Establish fine-grained security and access-control patterns using RBAC/ABAC principles, IAM integration, least-privilege access, row/column controls, masking, encryption, secure sharing, and auditability. Architect enterprise data-quality controls and observability, including validation rules, quality metrics, reconciliation, freshness/completeness monitoring, lineage, exception management, and SLA/SLO reporting. Design high-performance batch and streaming pipelines using Databricks capabilities and distributed processing patterns; establish reusable frameworks, engineering standards, and orchestration practices. Provide architecture for governed data exposure through APIs, Delta Sharing / secure data sharing, semantic layers, BI tools, ML/AI consumers, and downstream analytical applications. Translate business and governance requirements into conceptual, logical, and physical data models; define modeling standards for lakehouse, dimensional, and enterprise data structures. Serve as the first architecture point of contact for new projects and enhancements; lead discovery,…