Job Description

Location: Seattle preferred, remote is fine

Duration: 6 to 12 Months

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.

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