Permanent Data Engineer Jobs in New York
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AI Engineer
Applied AI EngineerNYC, hybrid We're partnered with a leading quantitative investment and technology firm that is building out a new generation of AI-powered tooling and looking to hire an AI Engineer to help drive the initiative.This is a highly hands-on role focused on identifying real business problems and building AI-driven solutions that impro...
Mortgage Analytics Developer
Mortgage Analytics Developer - Fixed Income and MortgagesOur client is a highly respected New York-based alternative asset manager focused on structured credit, mortgages, and asset-backed investments. The team combines deep fundamental credit expertise with sophisticated quantitative analytics and technology, providing direct exposure to portfoli...
Data Analyst
Data Analyst | Quantitative Trading FirmOverviewJoin a leading quantitative trading firm where data, technology, and research drive business performance.Work with large-scale financial, market, vendor, and alternative datasets that support critical business and research functions.Partner with engineers, data professionals, and business stakeholders...
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Lead Data Engineer
ResponsibilitiesLead the development of cloud-based data platforms, pipelines, and data products leveraging Python, SQL, Snowflake, and AWS.Build scalable solutions for a variety of data sources, including market, alternative, and enterprise datasets.Enhance the firm's data platform through APIs, automation, metadata management, and emerging AI-dri...
Lead Data Engineer
ResponsibilitiesLead the development of cloud-based data platforms, pipelines, and data products leveraging Python, SQL, Snowflake, and AWS.Build scalable solutions for a variety of data sources, including market, alternative, and enterprise datasets.Enhance the firm's data platform through APIs, automation, metadata management, and emerging AI-dri...
Senior Data Engineer
ResponsibilitiesBuild and optimize scalable data pipelines and data products.Develop reliable datasets for analytics, reporting, and AI applications.Establish data engineering standards, frameworks, and best practices.Improve data quality, monitoring, testing, and platform observability.Integrate and reconcile complex datasets from multiple sources...