Lead Data Engineer - Big Data Pipelines & ML Enablement

Federal Express Corporation; Plano (TX); Híbrido; USD 131.000 - 177.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Vision insurance

Dental insurance

Retirement plan

Tuition reimbursement

Descripción de la vacante

Federal Express Corporation is seeking a senior data engineer to take end-to-end ownership of critical data initiatives in a hybrid Plano, TX role. You will drive scalable data pipelines, implement advanced data engineering assets, and champion modern tooling and best practices across projects.

The role requires seven years of experience in data engineering and analytics, plus a strong background in ML frameworks, CI/CD, and information systems.

Formación

• Seven years or more of experience in measurement and analysis, quantitative business problem solving, or predictive analytics.
• Extensive knowledge in data engineering and machine learning frameworks, and design/implementation of large batch or online data pipelines.
• Strong understanding of information systems and complex systems in transportation or related industries.

Responsabilidades

• Owns end-to-end data engineering initiatives and validates scalable architectures.
• Advances capabilities using cutting-edge data engineering tools and methods across platforms and products.
• Leads design, build, test, and maintenance of data pipelines at big data scale; oversees batch processing for analytics readiness.

Conocimientos

Data engineering

Machine learning

Leadership

CI/CD

Communication to senior audiences

Educación

Bachelor’s degree in information systems/CS/math/engineering

Descripción del empleo

Federal Express Corporation is seeking a senior data engineer to take end-to-end ownership of critical data initiatives in a hybrid Plano, TX role. You will drive scalable data pipelines, implement advanced data engineering assets, and champion modern tooling and best practices across projects.

The role requires seven years of experience in data engineering and analytics, plus a strong background in ML frameworks, CI/CD, and information systems.