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CFS

Data Lake Analyst Job at CFS in Columbus

CFS, Columbus, OH, US

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Job Title: Data Lake QA & Power BI Analyst

Any additional information you require for this job can be found in the below text Make sure to read thoroughly, then apply.
Location: Columbus, OH
$83,000 - $115,000

About the Role

We are seeking an experienced contractor to support the final stages of a data lake implementation and lead the development of Power BI dashboards and reports. This role is ideal for a detail-oriented data professional with strong validation, testing, documentation, and analytics experience.

Key Responsibilities

  • Support the validation phase of a data lake project, including extensive testing, data verification, and quality assurance activities.

  • Document validation results, workflows, issues, and resolutions with a high degree of accuracy.

  • Collaborate with internal teams to ensure data accuracy, completeness, and readiness for reporting.

  • Design, develop, and implement Power BI dashboards, reports, and visualizations based on the finalized data lake.

  • Translate business requirements into actionable reporting solutions.

  • Troubleshoot data discrepancies and support continuous improvement of data quality and reporting outputs.

  • Communicate progress, issues, and recommendations clearly to stakeholders.

Required Skills & Experience

  • Proven experience working with data lake projects, preferably in the validation or testing phase.

  • Strong understanding of data structures, data modeling, and ETL concepts.

  • Hands-on experience developing Power BI dashboards, including DAX, data modeling, and performance optimization.

  • Excellent documentation skills and attention to detail.

  • Ability to collaborate across technical and business teams.

  • Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

  • Experience with Azure Data Lake or similar cloud data platforms.

  • Background in QA/testing within a data or analytics environment. xrczosw

  • Familiarity with SQL, data governance principles, and BI best practices.

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