Permanent Data Architect Jobs in New York
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Quantitative Developer Systematic Investing Platform
A leading quantitative investment firm is seeking an experienced software engineer to build and enhance the technology stack that supports systematic research and trading. The team develops platforms and tools used by quantitative researchers and portfolio managers to generate, test, and deploy investment strategies at scale.This is a highly collab...
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...
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...
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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...
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...
