Data Quality Analyst

Key Responsibilities● Audit & Validation: Conduct rigorous quality checks on scraped outputs fromStreamlit applications to ensure high-fidelity extraction from source documents.● Data Remediation: Utilize purpose-built data pipelines to manually orprogrammatically overwrite inaccurate data points discovered during auditing.● Pipeline Monitoring: Collaborate with data engineering teams to identify systemicscraping errors and refine the logic within the ingestion layer.● Governance Integration: Transition successful document auditing workflows intoour broader enterprise data governance practices.● Reporting: Maintain detailed logs of data discrepancies, /"ground truth/" comparisons,and error trends to inform future scraping strategies.Required Skills & Qualifications● Extreme Attention to Detail: You must have a passion for /"hunting/" for smalldiscrepancies in large datasets.● Snowflake Proficiency: Hands-on experience querying and managing data withinSnowflake is required.● Strong SQL Skills: Ability to write complex queries to validate data across multipletables and identify outliers.● Analytical Mindset: Experience auditing unstructured data (PDFs, images, or webscrapes) and comparing it against structured outputs.● Communication: Ability to clearly document data issues and explain technicaldiscrepancies to both engineers and stakeholders.Preferred Qualifications● Python Experience: Familiarity with Python for data manipulation (Pandas) or basicautomation is a significant plus.● Streamlit Familiarity: Understanding how Streamlit apps function to bettertroubleshoot how data is being captured.● Governance Background: Prior experience working within a formal DataGovernance framework or using data cataloging tools.

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