Apple Service Engineering (ASE) team needs to uncover insights that enhance data quality, strengthen engineering perfection, and ensure data products deliver value across every use case. They are seeking a Manager, Data Investigations to lead and grow a team of highly skilled analysts to drive strategic initiatives, foster innovation, and ensure the delivery of actionable insights for data problems outstanding to ASE.
Requirements
- Proficiency in SQL, Python, and visualization tools such as Tableau or Keynote.
- Strong understanding of statistical analysis and data modeling.
- Hands-on experience with big data technologies (Spark, Hive, Flink, Airflow, etc.).
- Familiarity with cloud environments and container technologies (e.g. Kubernetes).
- Background in developing scalable data pipelines and automation solutions.
Responsibilities
- Ensure high-quality analytics results — from root cause and impact analysis to automated dashboards and monitoring solution to find deep insights about data understanding.
- Guide your team in applying statistical methods, data science models, and advanced analytics to complex data challenges.
- Oversee the development of data tools, pipelines, and automation to improve efficiency and scalability.
- Translate technical findings into clear, impactful recommendations to engineering and data product leaders.
- Review and provide feedback on analytical methods, modeling approaches, and data visualizations.
- Champion data quality in analytics engineering processes.
- See opportunities to improve emerging tools and technologies in big data, cloud, and machine learning.
Other
- Lead, mentor, and inspire a team of Data Investigation analysts.
- Partner with multi-functional leaders in data engineering, data science, data product to set analytical strategy and priorities for their data quality initiatives.
- Foster a culture of continuous learning, collaboration, and innovation.
- Manage day-to-day operations, workload distribution, and career growth of the team members.
- Align data quality initiatives with broader ASE and Apple business goals.
- Build relationships across engineering, researchers, product, and leadership to ensure data quality is integrated into data products.
- Excellent communication skills — able to explain complex data findings to technical or non-technical collaborators
