The ETS-Insight Analytics Engineering team serves Apple's global manufacturing and operations analytics needs, providing enterprise-scale data platforms and analytics capabilities that process petabytes of data daily. As the Partner Success Engineering Manager, you will lead a partner-facing engineering team that serves as the strategic bridge between our data platforms and key business organizations—from Hardware Engineering to Operations and AppleCare. In this role, you will focus on understanding partner workflows, shaping their short- and long-term analytics vision, and ensuring our technical engagements directly drive measurable business value, operational efficiency, and smarter decisions.
Minimum Qualifications
Bachelor's or Master's degree in a relevant field (Business, Information Systems, Engineering, Computer Science, Analytics, or equivalent experience).
4+ years of experience leading, managing, or building engineering, technical solutions, or technical partner/customer success teams.
8+ years of overall experience working across data analytics, business intelligence, technical product management, or solutions consulting environments.
Strong technical fluency and conceptual understanding of modern data ecosystems, cloud platforms (AWS or GCP), data warehousing, and big data architectures (e.g., Spark, Trino, BigQuery, Iceberg).
Proven track record of working with business stakeholders to define requirements, quantify business impact (ROI), and deliver data-driven solutions.
Preferred Qualifications
Background in Partner Success Management, Technical Account Management, Solutions Architecture leadership, or Data Product Management.
Exceptional executive communication, stakeholder management, and cross-functional leadership skills.
Experience working with manufacturing, supply chain, hardware engineering, or operations organizations where analytics directly influences business decisions.
Ability to bring simple, logical, and business-focused approaches to complex multi-stakeholder challenges.
Demonstrated experience establishing engagement models, partner onboarding playbooks, and self-service analytics frameworks.