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Hands-on Working knowledge of Microsoft 365 security suite (Defender for Endpoint, Information Protection, Purview, DLP, EOP, Intune (MDM/MAM) and Defender for cloud Apps). Hands-on Working knowledge of Azure-native/cloud-friendly authentication mechanisms (OAuth, OpenID, etc) and experience with IAM, MFA, PIM/PAM, SSO for cloud and custom IDPs.
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Develop and optimize big data processing using Spark and PySpark within the Databricks environment. You should possess strong technical skills in SQL, Python, Spark, and PySpark and have hands-on experience with AWS and Databricks platforms.
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P Position Summary Hands-on Working knowledge of Azure-native technology stack like Azure AD, Defender for cloud (CSPM) & Identity, PIM, Conditional Access, Defender for Identity, AIP, Azure Log Analytics, Azure Monitoring, Azure Key Vault, Hands-on Working knowledge of Microsoft 365 security suite (Defender for Endpoint, Information Protection, Purview, DLP, EOP, Intune (MDM/MAM) and Defender for cloud Apps.
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We leverage leading technology stacks like Microsoft Azure, AWS, Google Cloud, Microsoft Power BI, Anaplan, Qlik, Tableau, SAS, Cloudera, Redhat and many others - to match your business goals with optimum technology solutions for all your stakeholders.
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The ideal candidate will have a strong background in SQL Server development, hands-on experience with Azure Pipeline, and proficiency in working with Databricks for data processing and analytics.
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Minimum 5 years’ experience in data engineering with a proven track record in the Azure ecosystem and with Azure DevOps. Minimum 5 years’ experience with Data Modeling, ETL, and Data WarehousingMinimum 3 years’ hands on experience with Azure Services.
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Minimum 8 years of designing and implementing an operational production grade large-scale data solution on Microsoft Azure Snowflake Data Warehouse. Including hands on experience with productionized data ingestion and processing pipelines using Python, Data bricks, Snow SQL.
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1-3 years of end-user support/desktop support: Microsoft Windows, Microsoft Office, desktop and mobile device troubleshooting, deployment of home networks 2-3 years of implementation and support of cloud products: Microsoft 365, Box, Dropbox, SharePoint / OneDrive, Azure, Intune, Conditional Access.
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The Desktop Support Engineer - Microsoft, Azure, O365 will provide desktop support and end-user server administration for all client issues while responding to Level 1 and 2 service tickets.
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Deep understanding of Microsoft Azure & Synapse/Fabric, SnowFlake, AWS and other large data platform technologies. Experience working for Top 10 Accounting or other Systems Integrator Services firms (Cognizant, TCS, Infosys, Capgemini, etc ) with a focus on Data, finance, ERP and/or digital solutions a significant plus.
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Demonstrated proficiency and hands-on experience in architecting, implementing, and managing Cloud-native database solutions, e.g., Azure SQL Database, Azure SQL Managed Instance and Oracle Cloud Infrastructure (OCI) Autonomous Data Warehouse, including deployment, configuration, and optimization.
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A software engineering industry certification, including but not limited to: Certified Scrum Developer (CSD), Certified Scrum Master (CSM), Certified Software Development Professional (CSDP), Certified Secure Software Lifecycle Professional (CSSLP), Amazon Certified: AWS Certified Developer, Microsoft Certified: Azure Developer, Certified Software Test Professional (CSTP.
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Modern Management - Mobility and Security Solutions in any of the following: Microsoft Intune; Autopilot, Desktop Analytics, Conditional Access, identity governance, Azure Active Directory (AAD), Microsoft Cloud App Security (MCAS); Advanced Threat Analytics; Defender for O365, Microsoft Endpoint Configuration Manager.
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At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) 4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) New York City (Hybrid On-Site): $201,400 - $229,900 for Lead Data Engineer.
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Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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hands on microsoft azure data processing jobs Title: applied scientist in New York, NY
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