Analyst, Data Integrity (Marketing Analytics Required)

Burbank, CA (Hybrid)

$60K/yr – $71K/yrMid LevelFull time

Posted 3 months ago

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Job Summary

Own data governance and taxonomy standards across marketing platforms within a Disney-focused analytics environment.

  • Must-have: Experience with data quality, analytics tooling, and data warehouses (e.g., Alteryx, Redshift/Snowflake).
  • Standout: Cross-functional collaboration with leadership and Data Operations to improve data processes.

Job Description

Responsibilities

  • Monitor marketing and analytics data to identify trends, anomalies, and errors
  • Partner with operations, planning, and analytics teams to troubleshoot and resolve data issues
  • Own and maintain marketing taxonomy standards to ensure consistent tagging and reporting across platforms
  • Manage taxonomy frameworks in Airtable and ensure alignment across systems
  • Use anomaly detection tools to proactively catch irregularities in campaign data and tagging
  • Support data validation, transformation, and workflow improvements using tools like Alteryx
  • Maintain strong oversight of data integrity and governance across marketing initiatives
  • Provide overflow support to the Marketing Analytics team with reporting, analysis, and troubleshooting
  • Collaborate with leadership, stakeholders, and Data Operations teams to improve data processes and documentation

Requirements

  • Bachelor’s degree in data science, statistics, computer science, marketing analytics, or a related field
  • Experience working with large datasets and maintaining data quality in analytics or marketing environments
  • Advanced Excel skills for analysis, auditing, and reporting
  • Experience with data visualization tools such as Tableau or Power BI
  • Familiarity with modern data warehouse environments (Redshift, Snowflake, or similar)
  • Experience with data workflow tools like Alteryx, Databricks, or similar platforms
  • Strong attention to detail and a systems-thinking mindset
  • Clear communication skills and the ability to collaborate across technical and non-technical teams
  • Curiosity, ownership, and a drive to continuously improve how data works

Preferred

  • Working knowledge of Python for data manipulation or automation is a plus