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# Lead Data/AI Engineering

- **Company:** AT&T Inc.
- **Location:** Plano, TX, United States
- **Experience:** Expert
- **Salary:** $170,000.0 - $237,400.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Apache HTTP Server, Microsoft Azure, BigQuery, Cloud Computing Security, Code Review, Computer Engineering, Continuous Integration, Information Engineering, Data Governance, Data Flow Control, Python (Programming Language), Machine Learning, Power BI, Tensorflow, SQL Databases, Tableau (Software), Azure Data Factory, Pytorch, Snowflake, Apache Spark, Git, Data Lakes, Scikit Learn, Information Technology, Collibra, AWS Glue, Apache Kafka, Software Version Control, Data Pipelines, Databricks
- **Published:** June 13, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=17a4e8a53854d436

## About the Role

Do you have experience in Version control systems?, Do you have a Bachelor's degree?, findings through technical documentation, dashboards (e.g., Power BI, Tableau), and presentations. Champion best practices in CI/CD, automation, and code review to continuously improve the performance, scalability, and reliability of the organization's data and AI ecosystem.

REQUIREMENTS: Requires a Bachelor's degree, or foreign equivalent degree in Computer Science, Computer Engineering or Data Science and 5 (five) years of progressive post-baccalaureate experience in the job offered or 5 (five) years of progressive post-baccalaureate experience in a related occupation utilizing Python and SQL for data engineering and AI/ML applications; using cloud platforms (e.g., AWS, Azure ) and data pipeline tools (e.g., Apache Spark, Airflow, Databricks); working with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn); utilizing CI/CD and version control systems (e.g., Git).

## Description

DUTIES: Design, develop, and optimize advanced data pipelines using technologies such as Apache Spark, Kafka, Airflow, and cloud-native tools like AWS Glue, Azure Data Factory, or Google Dataflow to drive business insights and enable automation. Collaborate with data scientists, architects, and business stakeholders to transform raw data into actionable intelligence, while architecting and maintaining robust data solutions across data lakes, warehouses, and marts using platforms like Snowflake, Redshift, or BigQuery. Develop, deploy, and monitor AI/ML models with frameworks such as TensorFlow, PyTorch, and Scikit-Learn, and operationalize these models via APIs and batch or streaming services. Ensure data quality, security, and compliance by applying best practices in data governance, encryption, and access control, leveraging tools such as Apache Atlas, Collibra, or cloud security features. Research and prototype cutting-edge AI/ML algorithms, evaluate emerging technologies, and communicate


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