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# Lead Data/AI Engineering - Platform Engineer

- **Company:** AT&T Inc.
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Salary:** $158,200.0 - $237,400.0
- **Contract:** Permanent contract
- **Skills:** HTML, JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Component-Based Software Engineering, Automation of Tests, Microsoft Azure, Cascading Style Sheets (CSS), Cloud Computing, Cloud Engineering, Code Review, Information Systems, Continuous Integration, Information Engineering, Data Infrastructure, Decision Support Systems, Python (Programming Language), Key Management, Node.Js, Cloud Services, DataOps, Software Deployment, Software Engineering, SQL Databases, TypeScript, Workflow Management Systems, Enterprise Data Management, Data Logging, ReactJS, Snowflake, Backend, Fastapi, Build Management, Containerization, Infrastructure Automation Frameworks, Information Technology, Graphql, Data Management, Api Design, Streamlit Framework, Software Version Control, Data Pipelines, Docker, Databricks
- **Published:** August 30, 2026
- **Apply:** https://dejobs.org/x/x/674245AA3F90453AAFC583C48D9C9E4C/job/

## About the Role

Education/Experience: Bachelor's degree desired in Computer Science, Software Engineering, Data Engineering, Information Systems, or a related technical field. Equivalent professional experience will also be considered. Five or more years of related experience. Certification is required in some areas.

## Description

This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted. No relocation is offered.

Overall Purpose: Architect, develop, deploy, and optimize secure, scalable data platforms and analytical applications that transform trusted enterprise data into reliable decision support solutions. Apply modern data engineering, software development, cloud architecture, and operational practices to move analytical products from prototype through supported production use.

Key Roles and Responsibilities: Typical tasks may include, but are not limited to, the following:

 * Data Platform Engineering: Design and build reliable data pipelines, transformations, data models, semantic models, and serving layers that support reporting, predictive analytics, AI capabilities, and interactive applications. Implement orchestration, validation, reconciliation, data quality controls, lineage, and data contracts across source systems and consuming applications.
 * Application and API Development: Architect and develop secure backend services, APIs, and modern analytical applications using Python, SQL, Streamlit, React, TypeScript, JavaScript, HTML, CSS, or comparable technologies. Create reusable services and application components that provide intuitive, responsive, and accessible experiences.
 * Testing, Integration, and Deployment: Apply software engineering practices including automation, version control, code review, automated testing, documentation, and continuous integration and delivery. Containerize and deploy applications using Docker and approved cloud services while addressing environment configuration, authentication, authorization, secrets management, and security requirements.
 * Cloud Scalability and Operational Reliability: Design and optimize Azure or comparable cloud architectures based on security, reliability, scalability, performance, supportability, and cost. Establish monitoring, logging, alerting, health checks, recovery processes, release controls, and operational documentation for applications, APIs, pipelines, and data products.
 * Technical Leadership: Lead complex engineering initiatives from requirements through production operation. Partner with analytics, AI, platform, security, architecture, and business teams to manage technical risk, establish reusable engineering standards, mentor team members, and deliver measurable business outcomes.
 * Technologies: Demonstrate advanced experience with Python and SQL, modern data platforms such as Snowflake or Databricks, API development patterns such as REST or GraphQL, container technologies such as Docker, and cloud platforms such as Azure. Experience with Streamlit, React, TypeScript, Node.js, FastAPI, orchestration tools, infrastructure as code, and data observability is preferred.

Job Contribution: An experienced professional, recognized as an expert, who creatively resolves complex data, application, and platform challenges using broad and in depth technical knowledge. Leads significant projects with strategic autonomy, influences architecture and business decisions, mentors less experienced staff, and frequently collaborates with senior leadership.


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