Top Remote Senior Level Data Engineer Jobs in Washington DC,

As a Principal Software Engineer in AI/ML Integrations, you will design, develop, and deploy AI & ML integration pipelines within the elluminate platform. Collaborate with data science teams to streamline data management and analytics for clinical trials, while ensuring scalability, performance, and security. Contribute to architectural decisions and mentor junior engineers in a collaborative environment.

As a Senior Data Engineer, you will transform operational data into analytical data, perform data analysis, write schema changes, and maintain ELT pipelines. You will champion a data-driven culture and interface with internal clients to understand their data needs, alongside troubleshooting data issues.

As a Senior Analytics Engineer, you will design, build, and maintain data models, collaborate with various teams on data transformations and governance, and ensure high-quality data products. Your role will focus on leveraging tools like dbt and Snowflake to drive innovation and informed decision-making across the organization.

The Senior Machine Learning Engineer at Wasabi will advance AI technologies, develop computer vision algorithms, and implement NLP model fine-tuning. This role involves collaborating with teams for seamless machine learning integration, conducting testing, debugging, and ensuring reliable system operations.

As a Senior Data Engineer at Instacart, you will build and maintain data pipelines to support paid marketing campaigns, collaborating with cross-functional teams while ensuring high-quality scalable solutions. You will drive data-driven decisions and enhance marketing strategies.

As a Senior Machine Learning Engineer at Samsara, you'll develop ML solutions for physical operations, driving new initiatives and optimizing systems. Collaborate with engineering teams to create end-to-end ML applications while influencing industry practices and contributing to company culture.

The Sr. Data Engineer-GCP designs, develops, and integrates data applications on Google Cloud Platform. Responsibilities include building data processing systems, automating data pipelines, leading unit testing, adhering to quality standards, and implementing process improvements. The role leverages machine learning and collaborates with internal and external resources to support reporting and analytics needs.