Permanent Financial Technology Jobs
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Kubernetes Tech Lead
Must be based in the Continental United States8+ years of Platform Engineering, Infrastructure Engineering, SRE, DevOps, or Kubernetes Engineering experienceDeep hands-on experience building, scaling, and operating Kubernetes platforms in productionStrong understanding of Kubernetes architecture, networking, storage, security, and cluster lifecycle...
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...
Vice President of Engineering, Investment Data & Analytics
Vice President of Engineering, Investment Data & AnalyticsBoston, MA (Hybrid)Position OverviewLead the strategy, architecture, and delivery of enterprise data and analytics platforms that support investment research, portfolio management, and business intelligence initiatives.Partner closely with investment professionals, quantitative researchers, ...
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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...