Data Quality & Insights Analyst

Apple; San Diego (CA); On-site; USD 90,000 - 140,000; Full time

Job summary

Apple is seeking a data analyst who can own external reporting from instrumentation QA to business logic updates, ensuring accurate results for senior leadership.

You will build visual dashboards with Tableau, Looker, and Jupyter, work with large datasets using Spark SQL, and perform root-cause analyses. Collaborate across teams to surface data quality concerns early and translate findings into actionable insights for product decisions.

Qualifications

• 4+ years of experience with SQL.
• Basic understanding of Python for pipeline development.
• Strong data analysis, storytelling, and presentation skills.
• BSc in CS, EE, Information Systems, Analytics or related field.

Responsibilities

• Own external reporting, from instrumentation QA to business logic updates to report generation and validation.
• Build the daily quality pipeline, creating reporting to automatically monitor for regressions and surface data quality concerns early in the development cycle.
• Perform root cause analysis for identifying anomalous data points.
• Serve as an internal liaison to other teams to support knowledge sharing of our data and best practices for its use.
• Build visual reports and dashboards using Tableau, Looker, Jupyter, etc.
• Work with large volumes of data, extract and manipulate large datasets using Spark SQL.
• Communicate complex concepts and the results of the analyses in a clear and effective manner to senior management.

Skills

SQL

Python

Data analysis

Storytelling

Presentation

Education

B.Sc. in CS/EE/IS/Analytics

Tools

Tableau

Looker

Jupyter

Spark SQL

Job description

Apple is seeking a data analyst who can own external reporting from instrumentation QA to business logic updates, ensuring accurate results for senior leadership.

You will build visual dashboards with Tableau, Looker, and Jupyter, work with large datasets using Spark SQL, and perform root-cause analyses. Collaborate across teams to surface data quality concerns early and translate findings into actionable insights for product decisions.