Top Remote Senior Level Data Engineer Jobs in Kansas City, MO

As a Big Data DevOps Lead, you will improve efficiency in Big Data infrastructure, coordinate initiatives across teams, lead architecture design efforts, ensure system reliability, and support operational tools while also providing on-call support.

The Director of Consumer Insights & Data Analytics will lead efforts to understand consumer behavior, drive marketing activities through data insights, and develop tools and frameworks to optimize the customer purchase journey and enhance overall business strategies.

As a Sr. Data Engineer, you will develop and optimize ETL pipelines and scalable systems on Google Cloud Platform. Your role involves delivering high-quality solutions, collaborating with cross-functional teams, mentoring junior engineers, and leading initiatives while applying strong analytical skills in an Agile environment.

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 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 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.

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.