Top Data Engineer Jobs

As a Senior Machine Learning Engineer, you'll design and manage distributed services and pipelines for Underwriting & Credit, collaborate cross-functionally, adhere to high code quality, and mentor fellow engineers while tackling technical challenges and contributing to new machine learning applications.

The Machine Learning Infra Engineer will bridge the gap between data science and production systems by optimizing models for runtime performance, designing scalable MLOps pipelines, and implementing monitoring frameworks. They will work closely with data scientists to improve workflows and ensure reliability across the system, while also developing data versioning and deployment strategies.

As a Consultant on the Data Integration team, you will implement StrataJazz® for large health systems, communicate integration specifications, solve complex problems using SQL and Excel, and lead client training. You'll also collaborate with technical teams and contribute to strategic growth projects in a hybrid work environment.

The Data Engineer will be responsible for developing data pipelines, data storage, and data lake solutions for enterprise-wide use. They will work closely with business groups to ensure timely and useful data assets and provide expertise in data engineering best practices.

Build robust data solutions and data pipelines for a real estate MLS workflow and data platform. Collaborate with cross-functional teams to enhance data infrastructure and quality. Shape data engineering team standards and culture. Work in New York City office.

The Data Engineer will work closely with Enterprise Architecture and Technology Leadership to design and implement modern data infrastructure on Azure. Responsibilities include developing data models, migrating data workloads, defining requirements for stakeholders, and collaborating throughout the entire delivery lifecycle.

The Senior Data Engineer will design and implement ETL processes in a cloud environment, develop monitoring solutions, document datasets, and collaborate with the Data Science team. This role requires building ETL processes and a strong understanding of data modeling.