Top Remote Data Engineer Jobs in Buffalo, NY

The Senior Machine Learning Engineer at Wasabi will advance AI technologies, develop computer vision algorithms, and implement NLP model fine-tuning. This role involves collaborating with teams for seamless machine learning integration, conducting testing, debugging, and ensuring reliable system operations.

As a Senior Data Engineer at Instacart, you will build and maintain data pipelines to support paid marketing campaigns, collaborating with cross-functional teams while ensuring high-quality scalable solutions. You will drive data-driven decisions and enhance marketing strategies.

As a Senior Machine Learning Engineer at Samsara, you'll develop ML solutions for physical operations, driving new initiatives and optimizing systems. Collaborate with engineering teams to create end-to-end ML applications while influencing industry practices and contributing to company culture.

The Sr. Data Engineer-GCP designs, develops, and integrates data applications on Google Cloud Platform. Responsibilities include building data processing systems, automating data pipelines, leading unit testing, adhering to quality standards, and implementing process improvements. The role leverages machine learning and collaborates with internal and external resources to support reporting and analytics needs.

Lead data engineer role at Wipfli focusing on the continuous advancement of a modern data lakehouse. Responsible for translating requirements into effective data models, developing in data technologies, managing project life cycle activities, achieving/maintaining proficiency in required skills, and collaborating with team members.

As a Senior Machine Learning Engineer, you will design data pipelines, develop machine learning models, and collaborate with various teams to integrate ML capabilities into products. You will also train others, conduct experiments to validate outcomes, and serve as a thought leader in data-driven innovations.

The Senior Data Engineer will design and architect data pipelines and ETL processes, maintain data lakehouse solutions, optimize data strategies across cloud platforms, mentor junior engineers, and ensure the high availability of data infrastructure while collaborating with data scientists for advanced analytics initiatives.