Data and MLOps Engineer

Position Overview

DPR is seeking an experienced Data & MLOps Engineer to join our Data and AI team. In this role, you will be instrumental in designing and implementing scalable, cloud-native solutions that power DPR’s AI initiatives. Working closely with cross‐functional teams—including business stakeholders, data engineers, software developers, data scientists, and product teams—you will build and support data pipelines and ML infrastructure that enable high-impact analytics and AI workflows.

DPR Construction is a leading, forward-thinking, self-performing general contractor specializing in technically complex and sustainable projects. We integrate cutting-edge technologies into the construction process, streamline operations, and drive innovation. Join us to be part of a team that is recognized as a great place to work and is committed to shaping your future.

Key Responsibilities

• Design distributed, cloud-native, scalable architectures for data and ML pipelines.
• Develop CI/CD pipelines and pipeline templates for Data Engineering, AI/ML, and Data Science teams.
• Automate the training, testing, and deployment processes for machine learning models.
• Develop and maintain ETL pipelines to move data in real-time/stream, on-demand, and in batch, with emphasis on security, reusability, and data quality.
• Leverage Infrastructure-as-Code platforms (e.g., Terraform, Bicep) to automate infrastructure provisioning and streamline deployments.
• Implement and manage APM and observability tools such as Azure App Insights or Datadog to monitor ML workloads.
• Contribute to preventive maintenance, technical debt reduction, and the promotion of clean code principles.
• Manage and maintain cloud infrastructure in both Azure and AWS environments.

Required Qualifications

• Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field.
• 3-5 years of experience in Data Engineering, DevOps, MLOps, Software Engineering or Site Reliability Engineering.
• Strong understanding of cloud infrastructure and experience with at least one major cloud provider.
• Excellent troubleshooting and debugging skills, with a focus on data integrity and system optimization.
• Proficiency in at least one object-oriented programming language, preferably Python, and practical experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Proficiency in SQL, with preference for Snowflake SQL.