Lead Data/AI Engineering

AT&T•Dallas, TX

1d•$158,200 - $237,400•Onsite

About The Position

The Lead Data/AI Engineering role helps shape how data and AI are leveraged across the enterprise to enable smarter decisions, faster innovation, and scalable AI adoption. This is a full-time onsite role performed at the designated work location five days per week; relocation is not offered. The role designs, builds, deploys, and supports production-grade Databricks applications connecting enterprise data, AI capabilities, and business workflows, using HTML for user interfaces and SQL for data access and transformation. It also develops and operationalizes AI and machine learning solutions, scalable ETL and data pipelines, and integrations across Snowflake, Azure, ADLS, Databricks, APIs, and other enterprise data platforms. The position implements MLOps practices for monitoring, evaluation, and lifecycle management; partners with business and technical stakeholders to translate use cases into technical designs; and supports data integrity, security, compliance, responsible AI, and enterprise risk management. The role requires lead-level experience delivering complex data and AI solutions, strong cross-functional communication, and an interest in applying emerging technologies thoughtfully in production. A bachelor's degree, such as in Computer Science or Scientific Computing, is desired. Five or more years of related experience are required, and certification is required in some areas. The position has no direct reports. The stated annual salary range is $158,200–$237,400, with individual starting salary dependent on factors including geography, experience, expertise, and education or training. The role is based in Dallas, Texas, and has a 40-hour workweek.

Requirements

Hands-on experience building, deploying, and supporting Databricks applications, including integrating data sources, developing user interfaces, and delivering applications for business users.
Proficiency in Python, SQL, and HTML, with experience building production-grade data applications and AI solutions.
Strong SQL skills for querying, transforming, and integrating data.
Hands-on experience designing and supporting ETL processes and large-scale data pipelines for analytics and AI workloads.
Hands-on experience developing and integrating solutions using Snowflake and Azure, including data storage, processing, and secure access, and experience working with ADLS.
Practical experience supporting AI and machine learning solutions, including data preparation, integration, deployment, and operational considerations.
Strong analytical and problem-solving skills for troubleshooting complex data and AI pipeline issues end to end.
Demonstrated experience as a Lead or advanced data engineer, AI engineer, or in a similar role delivering complex data and AI solutions.
Experience delivering Databricks applications and AI-enabled solutions in enterprise environments.
Ability to work cross-functionally and communicate technical concepts clearly to technical and non-technical stakeholders.
Bachelor's degree desired, such as in Computer Science or Scientific Computing.
Five or more years of related experience.
Certification is required in some areas.

Nice To Haves

A passion for learning about emerging data, AI, and cloud technologies and applying them thoughtfully in production environments.

Responsibilities

Design, build, deploy, and support production-grade Databricks applications connecting enterprise data, AI capabilities, and business workflows, using HTML for user interfaces and SQL for data access and transformation.
Design, build, and operationalize AI and machine learning solutions that meet business needs and perform reliably and responsibly in production.
Design, build, and support scalable ETL and data pipelines for ingesting, cleaning, transforming, and serving data for analytics, machine learning, and AI workloads.
Develop and integrate solutions across Snowflake, Azure, ADLS, Databricks, APIs, and other enterprise data platforms.
Implement MLOps practices, including monitoring, evaluation, and lifecycle management, to maintain AI system accuracy, scalability, and reliability.
Collaborate with business partners and technical stakeholders to understand use cases, translate requirements into technical designs, and iteratively deliver data and AI solutions.
Support data integrity, security, and compliance throughout the data and AI lifecycle, including responsible AI practices and enterprise risk management standards.
Troubleshoot complex data and AI pipeline issues end to end.

Benefits

Medical, dental, and vision coverage
401(k) plan
Tuition reimbursement program
Paid time off and holidays, including at least 23 vacation days each year and 9 company-designated holidays, based on date of hire
Paid parental leave
Paid caregiver leave
Additional sick leave beyond what state and local law require may be available but is unprotected
Adoption reimbursement
Short-term and long-term disability benefits
Life and accidental death insurance
Supplemental benefit programs, including critical illness, accident hospital indemnity, and group legal
Employee Assistance Programs (EAP)
Employee wellness programs
Employee discounts of up to 50% on eligible AT&T mobility plans and accessories, AT&T internet and fiber where available, and AT&T phone