Top Senior Level Data Engineer Jobs

As a Staff Data Engineer at Ivans, you will design and implement scalable data pipelines using cloud-native technologies, optimize data infrastructure, support BI product development, and collaborate with stakeholders to ensure successful project outcomes. Additionally, you will implement data governance tools and automate data workflows for reliable operations.

The Senior Technical Curriculum Developer will create engaging technical learning content for customers, including hands-on labs and certification programs. They will collaborate with engineering and product teams, evaluate training needs, improve existing courses, mentor junior members, and utilize SQL and scripting for reports and data handling.

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 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.

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.