Top Data Engineer Jobs

The Machine Learning Engineer will design, implement, and evaluate Computer Vision and ML algorithms, focusing on object detection and tracking, while writing C++ for various environments including embedded Linux devices and cloud servers.

The Analytics Engineer will enhance the data capabilities of analysts and stakeholders by architecting data models, building data pipelines, improving data governance, and providing training. Key responsibilities include monitoring data health, developing analytic frameworks, and standardizing data processes across various domains like growth and finance.

The Senior Data Engineer will build and scale data systems to process large volumes of data, develop data pipelines, design and launch new data models, and collaborate with various teams to provide data insights. They will also mentor team members and drive value through effective data solutions.

The Principal Analytics Architect will lead the Tableau function and data strategy for the Marketing Intelligence Team at Morningstar. Responsibilities include developing analytics reporting suites, collaborating with cross-functional teams, building cloud data environments, mentoring junior analysts, and optimizing Tableau dashboards to drive marketing effectiveness.

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.

The Lead Data Engineer will establish a vision for data architecture and build scalable data models and pipelines. Responsibilities include optimizing foundational datasets, ensuring data quality, improving data infrastructure, building analytical dashboards, and mentoring junior engineers.

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.