Data Quality Analyst - Chicago, United States - Apex Systems

    Apex Systems background
    Description

    Data Quality Analyst

    Large Banking Client

    Hybrid 2-3x/week onsite in Chicago IL OR Denver CO

    12+ month contract

    On a W2 basis ONLY (no corp to corp or 1099)

    Pay: $50-$57hr W2

    Required Skills:

    • 4+ years' heavy Data Quality Analysis experience
    • SQL
    • BA experience
    • Data warehouse/data governance
    • Data visualization
    • Agile & Waterfall environment experience

    Data Quality Analyst will be responsible for examining complex data to optimize the efficiency and quality of the data being collected, resolving data quality problems as well as working with various enterprise level and local data management governance, data architecture, data engineering/development, and data quality teams. Will contribute to efforts to capture and manage data dictionaries/catalogue, data lineage, and all forms of business, technical and operational metadata within the Metadata Repository. Additionally, role will support data use governance activities, adherence to Enterprise Data Management policies, and data quality issue tracking and resolution activities.

    Responsibilities will include:


    • Strong Data Management and Metadata Analysis skills.


    • Experience with, and understanding of, implementing and measuring Data Quality and Controls.


    • Analyze, query and manipulate data according to defined business rules and procedures


    • Identify, compare, and resolve data quality problems.


    • Determine business impact level for data quality issues.


    • Ensure adherence to data quality standards.


    • Determine root cause for data quality errors and make recommendations for long-term solutions.


    • Evaluate large dataset for quality and accuracy.


    • Identify and remedy defects within the production process.


    • Recommend, implement and monitor preventative and corrective actions to ensure that quality assurance standards are achieved.


    • Monitor the quality of data


    • Evaluate large dataset for quality and accuracy.


    • Identify, compare, and resolve data quality problems