Data and MLOps Engineer

Job Description DPR is looking for an experienced Data and MLOps Engineer to join our Data and AI team and work closely with the Data Platform, BI and Enterprise architecture teams to influence the technical direction of DPR’s AI initiatives. You will work closely with cross-functional teams, including business stakeholders, data engineers, and technical leads, to ensure alignment between business needs and data architecture and define data models for specific focus areas. Data & MLOps Engineer DPR is a leading construction company committed to delivering high-quality, innovative projects. Our team integrates cutting-edge technologies into the construction process to streamline operations, enhance decision-making, and drive efficiency at all levels. We are looking for a Data & MLOps Engineer to join our team and contribute to developing robust data solutions to support our AI, Machine Learning and Data Science team. Position Overview The Data & MLOps Engineer will be instrumental in the design and implementation of scalable, cloud-native solutions to meet the growing needs of our Data and AI team. The successful candidate will demonstrate the ability to abstract complexity and create reusable, scalable patterns that accelerate development. The Data & MLOps Engineer will design, build and support the data pipelines and ML infrastructure that enable our teams to deliver reliable, high-impact analytics and AI workflows, collaborating closely with data engineers, software developers, data scientists and product teams. The role bridges Data Engineering and ML Operations, focusing on scalable data processing, robust deployment practices and continuous monitoring and improvement of production systems. Responsibilities Design distributed, cloud-native, scalable architecture for data and ML pipelines Develop CI/CD pipelines and pipeline templates to be used across Data Engineering, AI/ML and Data Science teams Automate 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 emphasizing security, reusability, and data quality Leverage Infrastructure-as-code platforms such as Terraform and Bicep to automate infrastructure provisioning and streamline deployments Implementation and management of APM and observability tools such as Azure App Insights or Datadog to monitor infrastructure, focusing on 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 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 working 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 with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn Proficiency in SQL, preferably Snowflake SQL #J-18808-Ljbffr Dormont Manufacturing Co