Databricks Platform Architecture

AT&T; Dallas (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

AT&T in Dallas is seeking an experienced Enterprise Databricks Architect to lead architecture and governance for Databricks on Azure and AWS, enabling data engineering, analytics, and AI/ML workloads. This onsite role collaborates with security, cloud, and engineering teams to design scalable, cost‑effective platform solutions and establish best practices across the enterprise.

You will define standards, administer accounts and workspaces, implement Unity Catalog governance, and drive platform

Qualifications

• Master’s degree in Computer Science or related field.
• 7+ years of hands-on experience architecting and administering production Databricks environments.
• Databricks and Azure/AWS certifications preferred.
• Enterprise Databricks platform architecture and administration across Azure and AWS.
• Strong Unity Catalog governance and Azure Data Lake Storage administration.
• Serverless Databricks experience and cost optimization.
• Experience with Genie and Lakebase implementations.

Responsibilities

• Define enterprise Databricks architecture, standards, and roadmap across Azure and AWS.
• Design and administer Databricks accounts, workspaces, compute, SQL warehouses, and serverless capabilities.
• Establish governance using Unity Catalog and data access patterns.
• Architect and administer Azure Data Lake Storage and related storage containers.
• Evaluate, implement, and support Databricks products including Delta Lake, AI/ML, Genie, and Lakebase.
• Guide secure adoption of Genie and Lakebase.
• Lead troubleshooting and performance tuning; establish compute policies and cost optimization.
• Develop IaC, APIs, automation, and CI/CD for platform provisioning.
• Collaborate with Enterprise Architects, security teams, and engineers to establish reusable patterns.

Skills

Databricks

Azure

AWS

Unity Catalog

Data Lake

Serverless

IaC

CI/CD

Python

SQL

Security

Education

Master’s degree in Computer Science

Tools

Genie

Lakebase

Delta Lake

Databricks SQL

Azure Data Lake Storage

Job description

This is a full-time onsite role based in the location(s) posted and is performed from the designated work location five days per week. No relocation is offered.

Join AT&T and reimagine the communications and technologies that connect the world. The Data Science team at AT&T leads transformation through data-driven decisions that enhance the customer experience and businesses worldwide. Leveraging one of the largest data sets available, we develop meaningful insights that drive continuous innovation. We utilize the latest technology to develop generative AI solutions with real business impacts. When you step into a career with AT&T, you won’t just imagine the future-you’ll create it.

You will provide hands-on architecture and technical leadership for the enterprise Databricks platform across Azure and AWS. Design, implement, administer, and optimize secure, scalable, reliable, and cost-effective platform capabilities supporting data engineering, analytics, and AI/ML workloads.

A typical day includes making platform design decisions, configuring and troubleshooting platform services, establishing governance and security controls, optimizing performance and cost, and partnering with engineering and business teams to adopt Databricks capabilities, including Genie, Lakebase, and serverless services.

Key Roles and Responsibilities

• Define the enterprise Databricks architecture, platform standards, and technical roadmap across Azure and AWS, aligning business needs with security, reliability, scalability, and performance requirements.
• Design and administer Databricks accounts, workspaces, compute, SQL warehouses, and serverless capabilities, including identity integration, access controls, networking, monitoring, and workload isolation.
• Establish governance using Unity Catalog, including permissions, data access patterns, lineage, and integration with enterprise security requirements.
• Architect and administer Azure Data Lake Storage and associated storage containers, including access controls, connectivity, lifecycle management, and integration with Databricks.
• Evaluate, implement, and support Databricks products and capabilities, including Delta Lake, data ingestion and transformation, workflow orchestration, Databricks SQL, AI/ML, Genie, and Lakebase.
• Guide the secure adoption of Genie and Lakebase, including access configuration, integration patterns, operational readiness, and appropriate business use cases.
• Lead hands‑on troubleshooting and performance tuning; establish compute policies, usage monitoring, and cost‑optimization practices for both serverless and other compute configurations.
• Develop repeatable platform provisioning and configuration through infrastructure as code, APIs, automation, and CI/CD.
• Collaborate with Enterprise Architects, security teams, cloud infrastructure teams, and engineers to establish reusable patterns, resolve technical trade‑offs, and guide production implementations.

Qualifications

• Master’s degree in Computer Science or a related field desired.
• 7+ of related experience, including substantial hands‑on experience architecting and administering production Databricks environments.
• Relevant Databricks and Azure/AWS certifications preferred, subject to applicable role requirements.
• Enterprise Databricks platform architecture and administration: Deep hands‑on production experience across Azure and AWS, including account/workspace architecture, networking, identity, compute, and operational support.
• Security, governance, and cloud storage administration: Strong Unity Catalog expertise and practical experience administering Azure Data Lake Storage, storage containers, permissions, and secure platform connectivity.
• Serverless, performance, and cost optimization: Hands‑on experience implementing and operating Databricks serverless capabilities, tuning workloads, troubleshooting issues, and managing consumption and cost.
• Databricks product expertise, including Genie and Lakebase: Practical implementation experience with Genie and Lakebase, supported by broad working knowledge of Databricks data engineering, SQL analytics, and AI/ML capabilities.
• Platform automation and technical leadership: Experience with infrastructure as code, CI/CD, Databricks APIs, and Python/SQL, combined with the ability to establish architectural standards and guide engineering teams.