Top Hybrid Data Engineering Jobs in New York City, NY

The Senior Data Engineer will build and optimize data pipelines, ensure data integrity, and collaborate with stakeholders to meet business requirements while implementing best coding practices.

The Senior Data Platform Engineer will design, maintain, and enhance Hinge's data platform, including data pipelines, monitoring systems, and user feedback incorporation while ensuring data quality and system reliability.

Lead the design and implementation of enterprise-scale Knowledge Graphs and Semantic AI solutions, integrating graph intelligence and Generative AI. Manage cross-functional teams in data architecture and governance.

Lead the development and implementation of data architecture strategies, mentor a team to deliver solutions, and collaborate with stakeholders to enhance resources while ensuring project success and quality outcomes.

As a Data Scientist Manager in Card Payment Fraud Prevention, you will lead a team to build and deploy machine learning models to combat first-party fraud, enhance customer safety, and optimize fraud capture rates by leveraging big data and advanced statistical methods.

The Director of Data Engineering will oversee the design, development, and maintenance of data infrastructure and pipelines, ensuring data quality and regulatory compliance while collaborating with various teams to support AI-driven innovations.

The Platform Intelligence Engineer designs and maintains data infrastructure to support decision-making, analyzes data for performance metrics, and collaborates with stakeholders to operationalize insights.

The Data Engineer will design and build scalable data systems, contribute to the architecture of the data platform, and collaborate with AI/ML engineers to enhance automation and intelligence in Canoe's systems.

The Senior Analytics Engineer will manage the analytics layer, owning dbt projects, orchestrating data pipelines, defining metrics, and ensuring data quality while mentoring the data team.

The role involves improving reconciliation processes, training, project management, and providing expert guidance on data flow and reconciliation tools. Responsibilities include conducting training sessions, ensuring compliance, and leading automation initiatives.