Top Data Engineer Jobs in Minneapolis, MN

As a Distinguished Data Engineer at Capital One, you'll drive adoption of technology, collaborate on data challenges, mentor talent, and influence stakeholders.

As a Data Engineer Associate at PNC, you'll assist in developing data solutions, perform data analysis, support data infrastructure, and ensure data security.

As a Data Engineer/Senior Data Engineer, you will build and optimize data solutions and AI initiatives, managing data pipelines and collaborating with teams to enhance data infrastructure.

As a Data Engineer, you will build data pipelines, APIs, and contribute to the core product's analytics while collaborating with cross-functional teams.

The Data Engineer will develop and maintain data pipelines, improve data quality, analyze datasets, and build data models to support business objectives.

The Senior Data Engineer will create scalable data pipelines and manage unstructured data for AI/ML workflows, ensuring data quality and supporting data solutions. Collaboration with cross-functional teams to meet business and security objectives is key.

As a GCP Data Engineer Manager, you'll lead data engineering projects, develop data architectures, mentor teams, and enhance data solutions for clients.

Senior Manager in data engineering at PwC, responsible for designing data architecture, leading projects, and ensuring compliance with data governance while mentoring teams and driving strategic project success.

As a Cloud Data & Analytics Engineer at PwC, you'll lead technology workstreams, mentor others, build client relationships, and develop scalable data solutions using cloud technologies.

Design and optimize data pipelines, work with structured/unstructured data, ensure data quality for analytics, and collaborate with data scientists.

The HR Data Engineer role involves designing data pipelines, managing HR data integrations, ensuring data quality, and collaborating with HR to enhance data-driven decision-making.

Design and implement scalable data orchestration and processes, optimize data operations, and support building various platform areas.

The Senior AI Platform Engineer oversees the AI assistant platform, managing upgrades, compliance, performance, and user training while ensuring optimal platform performance.

Lead the ML-Ops Team and develop analytic data products. Oversee data strategies, automate capabilities, and mentor team members to ensure operational success.

The Data Engineer will build and operationalize data solutions, analyze data sources, and collaborate with teams to ensure data quality and governance.

Lead design and delivery of data solutions in Adobe Experience Platform, optimize data models, mentor junior engineers, and drive strategy.

The Senior Data Engineer will build and enhance data solutions and AI initiatives, managing data architecture, ensuring data quality, and optimizing BigQuery solutions.

As a Data Engineer II, you will build and operationalize complex data solutions, perform data analysis, and collaborate across teams to enhance analytics capabilities.

The Epic Cogito Data Engineer will gather reporting requirements, design and develop reports, and provide post-implementation support in healthcare IT.

As a Data Engineer I, you will focus on building and maintaining CICD pipelines, implementing DevOps practices, and transforming analytics infrastructure to support AI/ML initiatives and improve operational efficiency.

Lead a team in developing data security solutions, prototyping features, and collaborating cross-functionally on technology projects.

The Data Engineer will process data, convert pipelines, collaborate with teams, and establish CI/CD practices utilizing big data technologies.

Lead the evolution of SimplePractice's data stack, building scalable systems for analytics, reporting, and product insights in a fast-paced environment.

The Data Engineer will develop and maintain data pipelines, optimize processes for healthcare datasets, and collaborate with technical stakeholders.

Design and build secure data pipelines, lead data architecture, collaborate across teams, ensure data quality, and mentor other engineers.