Top Data Engineer Jobs

The Data Engineer II collaborates with IT and business partners to manage data pipelines for analytics and quality. Responsibilities include developing data governance, supporting reporting processes, and improving business workflows through data insights and automation.

As a Data Engineer, you will prepare data for AI applications through ETL processes, ensuring data quality, cleansing, and compliance while developing data pipelines for model training and deployment.

Seeking a Data Engineer to work on a multi-year project to build a clinical data registry platform in the healthcare industry. Responsibilities include managing, optimizing, and expanding data infrastructure to impact patient outcomes positively.

The Data Analytics Engineer applies engineering best practices to public transit software systems and products. Responsibilities include writing production-quality software, creating unit and integration tests, delivering product features, structuring data for consumption by other departments, designing scalable systems, and ensuring data security and privacy. Preferred qualifications include experience with various programming languages and tools such as Elixir, Python, AWS Glue, Terraform, and Tableau.

Seeking an experienced Senior Analytics Engineer to build and activate company-wide data assets using Snowflake. Responsibilities include data modeling, metrics development, and enabling self-service analytics solutions. Must have 5+ years of relevant industry experience and expertise in SQL, Python, and data engineering tools.

Deepwatch is looking for a highly skilled Data Engineer to manage and optimize data architecture to support AI and machine learning models. The role involves collaborating with data scientists, AI engineers, and business stakeholders to meet technical and analytical needs, as well as performing data analysis and maintaining dashboards.

Seeking a VP, Data Science & ML to lead modeling and AI/ML initiatives across the enterprise. Responsibilities include setting strategic direction, managing existing models, collaborating on machine learning platform deployment, and leading a team.