Lead Data/AI Engineering

AT&T•Plano, TX

4d•Onsite

About The Position

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 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).

Responsibilities

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 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.

Benefits

Medical/Dental/Vision coverage
401(k) plan
Tuition reimbursement program
Paid Time Off and Holidays (based on date of hire, at least 23 days of vacation each year and 9 company-designated holidays)
Paid Parental Leave
Paid Caregiver Leave
Additional sick leave beyond what state and local law require may be available but is unprotected
Adoption Reimbursement
Disability Benefits (short term and long term)
Life and Accidental Death Insurance
Supplemental benefit programs: critical illness/accident hospital indemnity/group legal
Employee Assistance Programs (EAP)
Extensive employee wellness programs
Employee discounts up to 50% off on eligible AT&T mobility plans and accessories, AT&T internet (and fiber where available) and AT&T phone