Top Remote Data Engineer Jobs in Detroit, MI

As a Data Engineer at Kustomer, you will enhance the data architecture, streamline data ingestion, and provide insights for product decisions. Responsibilities include writing tools for data classification, conducting data analysis, debugging, and ensuring data pipeline integrity, while collaborating closely with stakeholders for data visualization and best practices implementation.

The Data Engineering Manager at Dandy will lead a centralized team, build scalable data infrastructure, and drive innovation by creating data processes and facilitating cross-team collaboration. This role focuses on optimizing data pipelines and fostering a data-driven culture within the organization.

The Big Data DevOps Lead will enhance Big Data infrastructure efficiency, coordinate inter-team initiatives, and lead architecture efforts. Responsibilities include maintaining system reliability, deploying monitoring tools, and implementing disaster recovery practices. On-call support for production systems is also required.

As a Data Engineer at Vetcove, you will design and maintain scalable data pipelines, integrate external data sources, and leverage advanced techniques like Large Language Models for efficient data management and analysis.

As a Part Time Student in Quality/Data Analytics, you will identify and analyze information to support issue resolution, develop tools for data analysis, participate in development assignments, and adhere to project plans and schedules.

As a Senior Data Engineer, you'll design and architect data pipelines and ETL processes, maintain a data lakehouse, implement cloud data strategies, and ensure high performance and availability of data infrastructure. You'll mentor junior team members and collaborate with data science teams to elevate analytics capabilities.

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.