Top Artificial Intelligence Data Engineering Jobs in New York City, NY

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

The role involves managing data pipelines for AI and quantitative research, focusing on L3 market data architecture and integrity, API development, and collaboration with researchers.

The Analytics Engineer will build data models and pipelines for reporting and analytics, improving data infrastructure for ML and AI products, and setting processes for data collection and analysis.

Build FLORA's data function: design warehousing and pipelines, define core metrics, create dashboards and analysis workflows, and collaborate with the Intelligence team on generation analytics to inform product and model evaluation.

The Data Engineer will manage and develop data warehousing solutions, implement ETL processes, and utilize SQL for data analysis and reporting. Experience in analytics tools and communication is essential.

Direct the data platform, develop ML systems for analyzing AI search behavior, and lead a data team while collaborating with product teams.

The Senior Analytics Engineer will build and optimize data infrastructure to drive data-driven decision-making, creating actionable insights for therapy and business teams.

Partner with GTM to translate business goals into technical requirements, design end-to-end automations and AI-agent workflows, prioritize accounts, maintain data integrity and governance, document data models and processes, and liaise across Marketing, Sales, Success, and RevOps to deliver scalable GTM systems and measure tool ROI.

Manage Unity Audience Hub lifecycle: integrate and model first-party data, build audience segments, support sales with measurement and insights, run clean-room collaborations, and drive cross-platform campaign measurement and reporting.

As a Data Engineer, you will build and own the data infrastructure, design pipelines, ensure data quality, and implement DataOps practices while collaborating closely with product and engineering teams.