Top Remote Data Engineer Jobs in Kansas City, MO

The Data Analytics Engineer will support reporting and analytics by exploring data, ensuring quality models, collaborating with teams, and maintaining the data warehouse. Responsibilities include developing documentation and enhancing business outcomes through data-driven insights.

As a Principal Database Engineer, you will design and develop core modules for a data integration and analytics cloud platform, work with the engineering team on web applications, ensure compliance with quality standards, and provide technical guidance and support to other engineers.

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 Data Science Co-op at Jellyfish, you will help develop algorithms, create machine learning models, and analyze data to provide insights for engineering teams. You will collaborate with customers and contribute to marketing efforts while exploring applied mathematics and machine learning.

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.

As a Principal Full Stack Engineer, you'll lead the design and integration of ad analytics and ad fraud products, manage the software development lifecycle, mentor junior engineers, and ensure best practices in a collaborative environment. You'll work with product teams to gather requirements, build scalable systems, and automate cloud infrastructure.

As a Senior Data Engineer at Babylist, you will enhance data platforms, focusing on building and scaling Machine Learning pipelines. Collaborate with cross-functional teams to deliver data-driven solutions that support product growth and innovation. An emphasis on robust, production-grade coding is essential.