onsite
Staff Data Engineer - The Hershey Company
Data Engineer
Lead the design and build of a scalable MLOps platform, enabling data science teams to deploy, monitor, and govern ML models at enterprise scale using Python, Docker, Kubernetes, AWS, Terraform, and CI/CD pipelines.
About the role
Key Responsibilities
- Architect and implement end‑to‑end MLOps pipelines that move models from experimentation to production at scale.
- Design and maintain containerized services (Docker, Kubernetes) and cloud infrastructure (AWS) for model training, serving, and monitoring.
- Develop and enforce CI/CD workflows, automated testing, and deployment pipelines using Terraform, GitHub Actions, and other tooling.
- Collaborate with data scientists, ML engineers, and platform teams to define best practices, governance, and security for model lifecycle.
- Lead the growth of the MLOps function, mentoring junior engineers and shaping engineering standards.
Requirements
- 10+ years of experience in data engineering or ML engineering with a strong focus on MLOps.
- Proficiency in Python, Docker, Kubernetes, and AWS services (SageMaker, ECS, EKS, S3).
- Hands‑on experience with Terraform, CI/CD pipelines, and automated testing frameworks.
- Excellent problem‑solving skills and ability to translate business needs into scalable technical solutions.
- Strong communication skills and a collaborative mindset for cross‑functional teams.
Skills
pythondockerkubernetesawsterraformcicd