Databricks Architect (Onsite Hybrid)

NTT DATA Services•Atlanta, GA

11d•$117,600 - $196,000•Hybrid

About The Position

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.

Requirements

Minimum 10+ years of experience in Data Architecture, Data Engineering, or enterprise data-platform delivery, including architecture leadership for large-scale data ecosystems.
Minimum 5+ years of strong hands-on experience with Databricks and modern lakehouse architecture, including production-scale implementation and optimization.
5+ years of deep expertise in Medallion Architecture (Bronze, Silver, Gold), Delta Lake, distributed data processing, Spark/PySpark, SQL, batch processing, and streaming architecture.
5+ years of strong experience with Databricks Unity Catalog and enterprise data-governance capabilities including cataloging, metadata management, lineage, data classification, ownership, access governance, and audit controls.
Minimum 5+ years of data-governance experience covering data quality, metadata, lineage, stewardship, data ownership, policy enforcement, privacy, security, and compliance controls.

Nice To Haves

Strong cloud architecture experience with AWS, Azure, and/or GCP, including IAM, networking, encryption, secrets, storage, security controls, and integration with Databricks.
Experience designing secure data-consumption patterns including APIs, data sharing, semantic layers, BI integration, and controlled self-service analytics.
Strong knowledge of conceptual, logical, and physical data modeling; experience with dimensional modeling and enterprise data-modeling standards.
Strong stakeholder-management skills with the ability to communicate architecture to business, engineering, governance, security, and executive audiences.
Demonstrated ability to influence cross-functional teams, lead architecture decisions, and operate as a front-facing architect during core U.S. business hours.
Ability to work onshore in Atlanta with a minimum of 3 days per week in the office.

Responsibilities

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, feasibility assessment, architecture reviews, requirements clarification, and solution alignment.
Partner with Information Security, Risk, Compliance, Privacy, and Data Governance teams to embed regulatory and enterprise controls into the Databricks platform and data-product lifecycle.
Drive migration and modernization of legacy data platforms and workloads to Databricks, including architecture assessment, workload rationalization, migration patterns, performance tuning, and cutover strategy.
Support production issue analysis and triage during onshore hours, helping resolve data-quality, security, performance, pipeline, and platform issues while minimizing business impact.
Mentor data engineers and architects, provide design oversight and architecture governance, and work with vendors/system integrators to ensure implementation compliance.