Data Architect Jobs
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Business Architect
We're looking for a Business Architect (m/f/d) to join the digital team of an international energy supplier. This isn't a traditional enterprise architecture role. You'll work hands-on where business and technology meet, turning complex commercial and financial processes into clear solution designs. You'll also use AI and automation to simplify and...
Senior Java Developer
Build the Future of Mortgage InsuranceOur client is reimagining mortgage insurance from the ground up, replacing legacy systems and manual processes with modern software, automation, AI, and cloud-native technology. Our mission is to build the industry's most technology-enabled mortgage insurer through innovative engineering and scalable platforms....
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...
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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...
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...
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...