Taxonomy, Data Quality Analyst

Role Overview

• Assist in maintaining and updating product taxonomy, category structures, and attribute schemas.
• Review classification logic to identify gaps, inconsistencies, or optimization opportunities.
• Collect input from internal partners and suppliers to support changes or enhancements to taxonomy structures.
• Support implementation of taxonomy and attribute standards, normalization rules, and data governance policies.
• Maintain documentation including data standards, metadata definitions, workflows, and process guides.
• Perform recurring data integrity checks and system audits to identify discrepancies and escalate findings.
• Track and report on data quality metrics to identify trends and opportunities for improvement.
• Execute data cleansing, validation, and exception-handling tasks.
• Partner with senior team members to investigate and resolve data quality issues.
• Run SQL queries for audits, validation, and operational reporting.
• Use Python or SQL-based tools to automate repetitive data tasks or perform data transformations.
• Support QA workflows related to taxonomy updates, attribute changes, and content revisions.
• Work with product content, engineering, supplier data, and business teams to improve data completeness and accuracy.
• Participate in meetings to share findings and gather requirements.
• Evaluate data gaps and assist in aligning SKU build processes with documented standards.
• Support continuous improvement of work processes to increase efficiency and reduce errors.
• Develop dashboards, scripts, or monitoring tools to track compliance with data standards.
• Prepare reports and presentations for leadership as required.

Requirements

• Bachelor’s degree in Information Science, Data Analytics, Business, Library Science, or related field.
• Strong analytical and problem-solving skills.
• Experience working with structured data, taxonomies, metadata, or content management systems.
• Proficiency with SQL; familiarity with Python or similar tools for data manipulation.
• Ability to manage details while balancing throughput, accuracy, and deadlines.
• Strong communication skills and comfort working across functions.
• Experience with product information management (PIM) or digital content systems (Preferred).
• Exposure to data governance, data quality frameworks, or taxonomy management (Preferred).
• Background in retail, distribution, or eCommerce environments (Preferred).
• Analytical thinking.
• Data accuracy and attention to detail.
• Collaboration and teamwork.
• Curiosity and continuous improvement mindset.
• Technical aptitude for tools, data structures, and automation.

Tech Stack

• Python
• SQL

Benefits

• Bulk product discounts and offers
• Professional development opportunities