Top Remote Senior Level Data Engineer Jobs in Minneapolis, MN

The Senior Data Engineer will design, develop, and maintain data pipelines and infrastructure, focusing on optimizing data for AI/ML models. Responsibilities include leading the creation of data warehouses, ensuring data quality, and collaborating with cross-functional teams to meet data requirements for machine learning applications.

Seeking a CDP Data Engineer with expertise in Adobe Experience Platform Real-Time CDP to extract, transform, and load data for unified customer profiles. Responsibilities include platform expertise, data extraction, transformation, and loading, query writing, and more. Requires 5+ years of experience in data pipeline architecture.

The Director of Consumer Insights & Data Analytics will lead efforts to understand consumer behavior, drive marketing activities through data insights, and develop tools and frameworks to optimize the customer purchase journey and enhance overall business strategies.

As a Sr. Data Engineer, you will develop and optimize ETL pipelines and scalable systems on Google Cloud Platform. Your role involves delivering high-quality solutions, collaborating with cross-functional teams, mentoring junior engineers, and leading initiatives while applying strong analytical skills in an Agile environment.

The Senior Data Engineer will develop and scale a high-traffic digital ad exchange, mentor junior engineers, implement software best practices, and contribute to the architectural strategy. Responsibilities include shipping features, optimizing performance, and enhancing the overall platform.

As a Senior Analytics Engineer at Forward Financing, you'll design and maintain data models, collaborate with various teams to enhance analytics platforms, ensure data quality, and integrate third-party data sources to support business decisions.

Headway is seeking a Senior Data Engineer to help create access to affordable, quality mental healthcare across the United States. This role involves collaborating on data infrastructure design, partnering with product/engineering for best practices, creating data pipelines for business insights, and building real-time data pipelines in coordination with the Data Science team.