Top Remote Data Engineer Jobs in Chicago, IL

The role involves designing, developing, and integrating high-priority data applications using GCP, focusing on data processing systems and pipelines. It requires strong knowledge of data modeling, ETL practices, and may involve team leadership and guidance while adhering to Agile methodologies.

As a Computer Vision/Machine Learning Engineer at Dandy, you will develop computer vision models for 3D scans, research and implement advanced methods, work with large datasets, and maintain MLOps pipelines. Your role will contribute significantly to improving dental technology and practices.

As a Data Engineer at Headway, you will design and implement data pipelines to support business decisions, improve data infrastructure, and collaborate with cross-functional teams in providing valuable insights from data. You will engage with product, engineering, and data teams to create efficient data processing systems.

As Director of Data Science and AI at Cisco Meraki, you will lead a growing team to apply quantitative methods and develop machine learning models that enhance customer value and drive product development. Your role will involve strategizing AI use cases, overseeing AI/ML solution deployment, and improving data infrastructure in collaboration with various partners across the organization.

As a Senior Backend Engineer focusing on the Machine Learning Platform, you will design and maintain scalable AI solutions, develop distributed systems, collaborate with product and engineering teams, and integrate AI innovations into product development.

As a Senior Data Engineer at Bombora, you will develop and maintain scalable ETL pipelines, optimize data processing systems, and design databases. The role involves troubleshooting production issues, mentoring other engineers, and establishing best practices while leveraging technologies like Python, Airflow, and GCP.

As a Senior Analytics Engineer at Spring Health, you will develop and maintain data models using dbt, ensure data consistency and quality, provide documentation for downstream teams, and collaborate with finance and analytics for business metrics. Your goal is to drive effective data access, model performance, and support high-quality insights.