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Data Quality Analyst – Creativity Apps | Apple

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Location: Multiple Locations (U.S.) | Work Mode: Full-time | Compensation: $134,800 – $245,800 | Posting date/time : February 10, 2026


Job Description

Role Summary

The Creativity Apps team is looking for a Data Quality Analyst to drive the quality delivery of data for the world-class tools behind Final Cut Pro, Logic Pro, iMovie, GarageBand, Pages, Numbers, and Keynote. You will focus on building a new data integrity framework and developing automated reports to increase the visibility of data health across the entire creativity ecosystem.

Key Responsibilities:

  • Own the end-to-end external reporting lifecycle, from instrumentation QA to business logic updates and report validation.
  • Build a daily quality pipeline to automatically monitor for regressions and surface concerns early in the development cycle.
  • Perform deep-dive root cause analysis to identify and resolve anomalous data points.
  • Design and build visual dashboards using tools such as Tableau, Looker, and Jupyter.
  • Extract and manipulate massive datasets using Spark SQL and other big data tools.
  • Serve as an internal liaison to share data best practices across cross-functional Apple teams.
  • Communicate complex analytical results and data health metrics to senior management.

Qualifications:

  • Strong problem-solving, analytical, and quantitative skills.
  • Adept at critical thinking and deconstructing complex technical problems.
  • Ability to transform personal insights into data-backed recommendations.
  • Technical orientation with the ability to learn new data environments quickly.
  • Strong sense of personal responsibility and attention to detail.

Job details made easy by trendtoday360

Position: Data Integrity & Quality Engineer
Industry Focus: Creative Software, User Analytics, Big Data Engineering
Core Technology: Spark SQL, Tableau/Looker, Data Pipelines, Instrumentation QA

✅ Job Summary and Focus:

This role at Apple is for a Data Guardian. Because millions of creators rely on apps like Final Cut Pro and Logic Pro, the focus here is on Instrumentation Fidelity. You aren’t just analyzing data; you are ensuring that the data being collected is accurate, consistent, and actionable. The core challenge is building the Daily Quality Pipeline—an automated “health check” for data that catches regressions before they impact business decisions. You will act as the bridge between Instrumentation Leads and Senior Management, ensuring that the insights driving Apple’s next-generation creative tools are built on a foundation of absolute data integrity.

📌 Key ATS Resume Keywords:

Data Quality Analyst, Data Integrity, Instrumentation QA, Spark SQL, Big Data, Root Cause Analysis, Tableau, Looker, Jupyter, Data Visualization, Regression Monitoring, Data Pipelines, Business Logic, Creativity Apps, Apple, Analytics, Quantitative Analysis.

💰 Compensation and Industry Insights:

The base pay for this role ranges from $134,800 to $245,800, with total compensation packages including Restricted Stock Units (RSUs) and performance bonuses.

In the context of the U.S. Data Science and Quality Engineering workforce for 2025-2026:

  • The “Data Quality” Boom: In 2026, the demand for Data Observability and Quality Analysts has increased by 19% as companies realize that AI and ML models are only as good as the underlying data health.
  • Racial Representation in U.S. Data Analytics: Based on 2025 labor data for “Data Analysts and Quality Engineers”:
    • White: 52.4%
    • Asian: 31.8%
    • Hispanic or Latino: 7.1%
    • Black or African American: 5.9%
    • Other/Multiracial: 2.8%
  • Gender in Quality Engineering: Women currently represent approximately 26% of the data quality and integrity workforce. Apple’s focus on “creative thinking and hard work” supports a high-performance, inclusive culture.
  • Big Data Standard: Experience with Spark SQL is now a critical differentiator; analysts proficient in distributed data processing command an average of 12% higher base salaries than those limited to traditional SQL environments.

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