Top Remote Data Engineer Jobs

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.

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.

As a Staff Machine Learning Engineer at Canva, you'll develop AI/ML strategies to enhance customer support, lead the creation of natural language understanding systems, and collaborate with teams to leverage ML capabilities while mentoring other engineers.

The Manager, Data Engineering will lead and mentor a team of six data engineers, oversee the design and development of Canoe's data platform, manage project timelines, and drive collaboration with product management. The role requires delivering data-driven solutions and adapting to complex technical challenges.

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.

The Data Engineer will design, implement, and maintain the data infrastructure for analytics and business intelligence at Endpoint. Responsibilities include developing ETL pipelines, managing data warehouses, ensuring data quality, and collaborating with cross-functional teams to optimize data workflows and support data-driven decision-making.

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.