AI-ML-Azure at Remote, Remote, USA |
Email: [email protected] |
From: Nirmala, Intellectt [email protected] Reply to: [email protected] Along with the Azure skillset we need person experience in Azure ML and AI skillset as well. Required skill set: Intermediate to expert level experience in Microsoft SQL Server - Writing Complex Queries; Debug existing Stored procedure; DB Performance improvement; Developing quality audits Intermediate level experience in PowerBI and Excel (VBA, Lookups, pivots, etc.) Working knowledge on Azure stack Synapse, Spark/Python, SQL Azure, Azure Data Factory (ADF) - Ability to quickly ramp up on Azure Experience working on project management tools like Azure DevOps (ADO), JIRA, etc. Excellent analytical and problem solving skills Ability to work in Agile environment, deal with ambiguity and critical thinking to achieve the expected results within SLAs Excellent communication skills and ability to work with customer stakeholders and cross-functional teams by effectively understanding the business requirements Preferred skills: Prior experience in Microsoft landscape or corporate finance space is preferred. Experience working with multi-geographical teams and in onshore-offshore model Willingness to learn new technologies. Job description: Write, test and schedule audits for data validations reports using SQL Stored Procedures, Views and Functions Collecting and analyzing large and complex data sets Validating data to ensure accuracy and completeness. Conducting ad-hoc analysis, solving data discrepancies, and generating actionable business insights. Extending support on production issues during non-business hours as needed. Understand data lineage, data quality and relationships. Monitor ETL jobs and respond to any job failures. Perform data engineering related activities e.g. developing and enhancing tools/solutions/processes based on data analysis and/or new customer requirements. Development support for platforms and applications assigned. Ability to work on Level 2 Service Requests from business users. Document knowledge base articles for Tier-1 and Tier-2 Dedicate 20%-30% of time for Development efforts Automation of operational activities, data quality checks, application feature development, develop tabular models, bug fixes and reporting. Work with customer stakeholders and team members for performance improvement and suggestions. Ramp-up on new Azure skills as per the project demands. Keywords: artificial intelligence machine learning database active directory AI-ML-Azure [email protected] |
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Tue Aug 06 19:57:00 UTC 2024 |