On Site Cloud Data Architect Jobs in New York
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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...
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...
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...
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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...
DevOps Engineer
1-6 years of experience in DevOps, Site Reliability Engineering (SRE), Platform Engineering, Infrastructure Engineering, or Cloud Engineering.Strong hands-on experience managing Kubernetes in production environments.Experience building, automating, and supporting AWS-based infrastructure.Proficiency with Infrastructure as Code tools, particularly T...
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...
