Lead Data/AI Engineering - Platform Engineer

About the role

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.

Responsibilities

• 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

Python, SQL, Snowflake or Databricks, REST or GraphQL, Docker, 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.

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.

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

Pay

Our Lead Data/AI Engineering jobs earn between $158,200.00 – $237,400.00 USD Annual. Individual starting salary within this range may depend on geography, experience, expertise, and education/training.

Schedule

40 hours per week. Office presence of a minimum of 5 days per week. Location: Dallas, Texas. No relocation is offered.