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    Data Engineer - Atlanta, United States - Xebia

    Xebia
    Xebia Atlanta, United States

    3 weeks ago

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    Description


    The Opportunity The Data Analyst will be a key part of the Enterprise Data Services team, which is responsible for transforming data from disparate systems to provide insights and analytics for business stakeholders.

    Specifically, this role will support a multi-year project to migrate legacy data jobs and reports owned by business areas across the company to cloud-based technology solutions and modern data tools.

    You will collaborate with Data Engineers, Data Analysts, DBAs, cross-functional teams, and business teams.

    You will analyze, classify, migrate or redesign data jobs/reports into modern data tools, using Agile methodology, that empower users to make informed business decisions.

    Progress will be documented and validated against current report outputs.

    [Note:

    Delta IT works in a rotating hybrid schedule with 2-3 days in the office per week - full remote work is not authorized].

    Qualifications

    Bachelor of Science degree in Computer Science or equivalent

    At least 5+ years of post-degree professional experience

    Required experience in SQL and other querying languages to into modern data tools or jobs

    Strongly preferred experience in data analysis to create, publish, and/or manage reports and data visualizations in Tableau, PowerBI, AWS Quicksight, or AWS DataZone (i.e., our target solutions)

    Highly desirable experience implementing performance tuning in Tableau dashboards

    Highly desirable experience working with TOAD data tool

    Demonstrated experience building and preparing data for analytics

    Proficiency working with database technologies and data development such as Python, PLSQL, etc.

    Experience working with queries/applications, including performance tuning, utilizing indexes, and materialized views to improve query performance

    Identify necessary business rules for extracting data along with functional or technical risks related to data sources (e.g. data latency, frequency, etc.)
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