Top Remote Senior Data Engineer Jobs in NYC, NY

The Data Engineering Manager will lead the development of core data pipelines, mentor junior engineers, collaborate across disciplines, and ensure user privacy. Responsibilities include task planning, recruitment, and maintaining technical accuracy in the team's work.

The Vice President of Data Intelligence Engineering will drive the execution of quarterly deliverables and long-term strategies while developing a world-class data platform. Responsibilities include ensuring data privacy and security, mentoring engineering teams, and collaborating with cross-functional teams to align strategies with company objectives.

As a Sr. Data Engineer at NBCUniversal, you will design and construct scalable data pipelines and analytics applications. You'll collaborate with diverse teams to gather data requirements, employ data modeling techniques, and optimize data architecture. Your expertise in cloud-based technologies and machine learning will guide your contributions to generative AI initiatives and support strategic decisions across the company.

As a Senior Data Engineer, you will develop and maintain scalable data platforms, architect high-volume data pipelines, improve system performance, ensure data privacy compliance, and collaborate with teams for operational efficiencies. You are expected to debug complex issues and share knowledge through documentation and mentoring.

The Senior Machine Learning Engineer will build scalable machine learning systems, enhance entity resolution algorithms, and develop ML infrastructure. Responsibilities include designing reliable ML solutions and collaborating with cross-functional teams to optimize performance and testability.

As a Data Engineering and Analytics Manager at Spark Advisors, you will lead the data function, overseeing the development of a data warehouse, implementing data products, and mentoring your team. You'll work closely with various teams to ensure efficient data processing and provide insights through analytics infrastructures and dashboards.

Develop and maintain core data models in dbt, ensuring consistency across business metrics. Collaborate with finance and data analysts, provide documentation for data access, drive data quality initiatives, and regularly audit data models for integrity.

The role involves building computer vision models for 3D scans, researching state-of-the-art machine learning methods, working with product and research teams to improve product lines, and implementing best practices for MLOps pipelines, all while working with large datasets.