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Johns Creek

    Sr. Data Engineer - Johns Creek, United States - Datum Software

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    Description
    *Sr. Data Engineer #37882
    • Atlanta, GA

    Top 5 Skillsets:
    Very Proficient in Teradata SQL
    Excel Proficient
    Python
    Experience with NodeJs Experience with CloudWatch insights/metrics
    Strong mathematical and statistical skills

    Additional Notes

    Experience with NodeJs
    Experience with CloudWatch insights/metrics
    Strong mathematical and statistical skills
    Analytical skills to gather, view and analyze information
    Numerical skills to measure and statistically analyze data
    Technical skills, including software and scripting languages, to organize and present data

    Using the above skills should have ability to review data and to determine how to solve problems using that data, and to learn critical insights about customers.

    Ability to communicate this information with key stakeholders, including company leadership.

    *Qualifications:

    Bachelor of Science degree in Computer Science or equivalent

    At least 7 years of post-degree professional experience

    At least 5+ years of Airline industry experience

    4+ years development experience building and maintaining ETL pipelines

    3+ years of experience working with database technologies and data development such as Python, PLSQL, etc.

    Experience in mentoring junior team members through code reviews and recommend adherence to best practices

    Deep understanding of writing test cases to ensure data quality, reliability, and high level of confidence

    Track record of advancing new technologies to improve data quality and reliability

    Continuously improve quality, efficiency, and scalability of data pipelines

    Expert skills 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.)

    Develop initial queries for profiling data, validating analysis, testing assumptions, driving data quality assessment specifications, and define a path to deployment

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