Linde Gas & Equipment Inc. Sr. Data Engineer Tonawanda, NY, United States | req31963 What you will enjoy doing* Architect, build, and maintain scalable, distributed data pipelines using Apache Spark and Microsoft Fabric to process large
Job Title This role will be based out of Buffalo NY or Rochester NY corporate office (4 days on site and 1 day remote) This role focuses on improving how the bank leverages data to drive
Technology Team Lead Location: Hybrid/Buffalo, NY (3 days onsite / 2 days remote) Duration: Contract to Hire This is a temp to hire position and will have direct reports. Person must be in Buffalo working hybrid
Maximus TCS (Technology and Consulting Services) Internal Job Profile Code: TCS220, T4, Band 7 Job-Specific Essential Duties and Responsibilities: - Execute CVE-based patching by severity across client, server, cloud, and on-prem environments. - Develop, test, maintain, and
Key Responsibilities: • Own and improve the reliability, availability, observability, and operational supportability of Maximus UKs Azure Databricks platform, Azure data services, and associated data pipelines and data products. • Design and implement monitoring, alerting, health checks,
Job Title: Lead Site Reliability Engineer Location: Remote within the USA, or onsite in Buffalo, NY / Wilmington, DE (client preference for candidates near these areas). New hires are required to work onsite at the clients
Essential Duties and Responsibilities: - Design and build customer experience and conversational AI solutions, including dialog flows, API integrations and AI agent orchestrations. - Develop and maintain technical integrations between solutions and Maximus technologies such as
Essential Duties and Responsibilities: - Perform hands-on data analysis and modeling with huge data sets. - Apply data mining, NLP, and machine learning (both supervised and unsupervised) to improve relevance and personalization algorithms. - Work side-by-side
Essential Duties and Responsibilities: - Perform hands-on data analysis and modeling with huge data sets. - Apply data mining, NLP, and machine learning (both supervised and unsupervised) to improve relevance and personalization algorithms. - Work side-by-side