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Software Engineering Manager, Data Investigation

Apple

Seattle, Washington, United StatesOn Site

Original Job Summary

Overview

People at Apple don’t just build products — they craft experiences that revolutionize entire industries. Join Apple and lead the Data Investigation team to uncover insights that enhance data quality, strengthen engineering, and drive value across our services.

Responsibilities

  • Lead, mentor, and inspire a team of Data Investigation analysts.
  • Partner with multi-functional leaders to set analytical strategy.
  • Ensure high-quality analytics from root cause analysis to automated dashboards.
  • Apply statistical methods and data science models to complex challenges.
  • Oversee development of data tools, pipelines, and automation systems.
  • Translate technical findings into clear recommendations.
  • Foster a culture of continuous learning and innovation.

Minimum Qualifications

  • BS in Computer Science, Engineering, Mathematics, or related field.
  • 8+ years of experience in data analytics, engineering, or related fields.
  • 3+ years in a leadership role.
  • Proficiency in SQL, Python, and visualization tools like Tableau or Keynote.
  • Strong understanding of statistical analysis and data modeling.
  • Excellent communication skills to explain complex data findings.

Preferred Qualifications

  • Experience with big data technologies such as Spark, Hive, Flink, and Airflow.
  • Familiarity with cloud environments and container technologies like Kubernetes.
  • Experience in commerce, payments, or large-scale online services analytics.
  • Background in building scalable data pipelines and automation solutions.

Key skills/competency

data analytics, SQL, Python, Tableau, Spark, Hive, Flink, Airflow, big data, leadership

How to Get Hired at Apple

🎯 Tips for Getting Hired

  • Research Apple's culture: Study their mission, values, news, and reviews.
  • Customize your resume: Highlight leadership and analytics skills.
  • Emphasize technical expertise: Include SQL, Python, and dashboard projects.
  • Prepare for interviews: Practice explaining complex data projects clearly.

📝 Interview Preparation Advice

Technical Preparation

Review SQL and Python fundamentals.
Practice using Tableau for data visualization.
Study big data tools like Spark and Hive.
Refresh statistical analysis and data modeling techniques.

Behavioral Questions

Describe a leadership challenge you overcame.
Explain a time you resolved data conflicts.
Discuss a strategy for team innovation.
Share an experience with cross-functional collaboration.