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    Azure/SQL Data Engineer/Analyst-Seattle, WA - Georgia IT Inc

    Georgia IT Inc
    Georgia IT Inc Seattle, United States

    2 weeks ago

    Default job background
    Description
    Azure/SQL Data Engineer/Analyst
    Location: Seattle, WA (Remote)
    Duration: 12+ Months
    Rate: DOE

    US Citizens and Green cards are Preferred.

    Technology:
    • SQL Server 2019 / Azure SQL, Good SQL & ETL skills.
    • Strong expertise on T-SQL and working knowledge on SSIS & ADF.
    • Strong knowledge on Excel - Pivots, PowerPivot, VBA .
    • Working knowledge of PowerBI.
    • Strong data analytical skills, understanding and experience in Data Quality.
    • Ability to make business conclusions from data, connect scenarios.
    • Background of working in an Agile / Sprint based work environment.
    • Knowledge on DAX scripting and BPC-Standard & Expense - recommendation.
    Additional skills:
    • Understanding Data Management & BI concepts, Data Analysis, Analytics, Cubes, Reporting Technologies, ETL.
    • Working knowledge/ concepts in Azure PaaS technologies - Databricks, ADLS / ADW / Synapse is a big plus.
    • Prior experience in Microsoft landscape is a big plus.
    • Ability to deal with ambiguity and work in agile environment.
    • Excellent communications skills with business users / stakeholders.
    • Attention to detail.
    • Strong troubleshooting skills.
    • Hands on experience with SharePoint.
    Responsibilities include:
    • Provides extensive troubleshooting and technical expertise in identifying data issues that impact data metrics.
    • Implements measures / solutions to proactively track data quality issues.
    • Gather and Confirms project requirements by studying user requirements, conferring with others on project team.
    • Participate in requirements / user acceptance tests/ business functionality tests.
    • Provides support to the users on any data related questions/issues reported.
    • Documenting processes, supporting partner teams, participating in user training.
    • Solving data discrepancies and providing business intelligence insights.
    • Monitor data extract, transform, and load (ETL) jobs and respond to any job failures.
    • Troubleshoot complex data related issues escalated from Tier 1.
    • Flexibility to support production issues during off hours.
    • Communication of ongoing issues / incidents to business community.
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