Top Hybrid Data Engineering Jobs in New York City, NY

The Staff Implementation Engineer will lead complex data integrations, develop big-data pipelines, and mentor engineers, ensuring high standards for data security and governance.

As a Data Engineer II at Magnite, you will build and optimize data pipelines with Apache Spark and Python, collaborate on data architecture, ensure operational performance, and work on infrastructure provisioning using Terraform and AWS.

The Senior Data Engineer will transform real-world data into analytics-ready datasets, build scalable pipelines, and conduct analyses to support scientific and business decisions, collaborating closely with data science teams.

The Senior Analytics Engineer will design data models, build data pipelines, and support analytics needs across teams, enhancing data infrastructure.

The Principal Data Engineer at NBCUniversal leads the development of data applications, manages data pipelines, and collaborates with teams while coaching junior engineers. Responsibilities include designing scalable data solutions and integrating AI technologies.

The Analytics Engineer will build data infrastructures, create dashboards, define metrics, structure datasets for AI projects, and foster insights across company functions.

Fora seeks a Senior Analytics Engineer to enhance data modeling and delivery, ensuring access to reliable insights across teams. Responsibilities include managing the analytics layer, improving data performance, and mentoring while collaborating with stakeholders on analytics needs.

Design and implement data management strategies, creating scalable data solutions, and collaborating with teams to address business challenges and ensure data integrity.

As a Senior Forward Deployed Accountant, you will architect and automate accounting processes, engage with CFOs, troubleshoot technical issues, and drive AI-driven transformation across enterprise accounts.

The Knowledge Systems Architect will design systems for knowledge organization, automate documentation processes, and enhance knowledge artifact legibility to support AI effectiveness in the R&D environment.