On Site Permanent Data Engineer Jobs in New York
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TechOps / DevOps Engineer
Your Future Role:Support and administer JFrog applications. Support and administer Atlassian Data Center applications. Investigate, triage, and resolve incidents, service requests, and user issues in a timely and professional manner. Monitor platform health, performance, availability, and usage trends across the development tooling estate. Contribu...
Technology Solutions Engineer
Technology Solutions EngineerNew York, NY | Hybrid (4 Days Onsite)We're partnering with a leading multi-strategy investment firm seeking a Technology Solutions Engineer to join a highly visible team supporting front-office users and business-critical technology platforms.This role sits at the intersection of production engineering, platform enginee...
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...
