Top Senior Level Data Engineer Jobs in Minneapolis, MN

As the Director of Data Science & AI, you will lead a team to develop AI and ML solutions that align with the business strategy. Responsibilities include overseeing the ML workflow, collaborating with Product and Engineering, and managing a high-performance team to drive customer-centric analysis and strategic initiatives.

The Senior Data Engineer at Spokeo will develop and optimize data technologies, build automation pipelines, collaborate with stakeholders to create data products, monitor performance, and follow data governance best practices.

As a Senior Software Engineer on the ML Platform team at Upstart, you will build and maintain software applications enabling machine learning models, develop infrastructure for model training, support automation, and collaborate with data engineers and scientists to enhance deployment processes.

As a Senior Machine Learning Engineer at Affirm, you will develop machine learning models for assessing creditworthiness, build training and monitoring systems, and collaborate with product and engineering teams. You'll implement data pipelines and drive innovations in credit decisioning with cutting-edge technologies.

The Data Engineering Manager will lead initiatives to improve Datasite's data architecture, oversee the development of data pipelines, and ensure high-quality data availability. This role involves collaborating with leadership to translate business needs into technical requirements, exploring new data tools, and managing a team focused on enhancing data observability and integrity.

The Data Quality Specialist will work on multidisciplinary project teams, focusing on data quality practices involving environmental and analytical data. Responsibilities include evaluating laboratory capabilities, preparing cost estimates, coordinating laboratory services, performing data assessment, and technical writing for quality assurance documents.

The SQL Database Administrator will monitor, maintain, and troubleshoot SQL databases for Q2's SaaS products, support customer implementations, perform maintenance during weekends, and participate in on-call support. The role requires critical thinking to resolve database issues and involves documentation of processes.