You will work within a fast-moving operational team supporting one of Apple's most complex and business-critical data platforms. Your work directly enables the Apple engineering and operations teams that build every Apple product. Own the end-to-end lifecycle of support requests — from understanding the end user's problem, through investigation and root cause analysis, to resolution and clear documentation that leaves the system better than you found it Communicate with confidence across a diverse customer base — internal Apple engineering and operations teams, as well as external manufacturing partners — translating technical findings into clear, actionable information for audiences at every level Lead through ambiguity: take ownership of complex, cross-functional issues on a large-scale data platform and drive them forward even when the full picture is not immediately clear; teams across the organization rely on the clarity and direction you provide Identify patterns across issues — surface systemic weaknesses, data quality problems, and recurring failure modes, and work with internal DevOps/SRE and engineering teams to address root causes rather than symptoms. Analyze and interpret data to support business decision-making, ensuring accuracy and integrity at every step; prepare clear reports and visualizations that give stakeholders genuine insight Conduct requirements gathering and contribute to platform improvement initiatives — you will interact directly with customers to understand their workflows, frustrations, and unmet needs Create and maintain documentation: SOPs, process flows, and knowledge base content that raises the baseline capability of the whole team Collaborate with testing and engineering teams on UAT, release validation, and feature feedback cycles — your customer proximity makes you a critical voice in how the platform evolves Contribute to a culture of continuous improvement — bring data, observations, and hypotheses to the team with the confidence to challenge what is not working There is opportunity to travel and work on-site with customers across EMEA and beyond — gaining direct exposure to how Apple's manufacturing partners operate and deepening the business context you bring back to the team
Minimum Qualifications
Proven experience in a technical support, business analysis, or data analyst role within a large-scale enterprise environment — L2/L3 support experience is a strong indicator
Good SQL skills and experience preparing reports and analysis using Excel or equivalent tools — able to write complex queries against large datasets, and translate findings into clear, structured outputs for business stakeholders
Clear, confident communication — written and verbal — with the ability to adapt your message for technical engineers, operational stakeholders, and senior business leaders equally
Analytical mindset: able to take incomplete or ambiguous information, form a structured hypothesis, and drive toward a conclusion.
Preferred Qualifications
Experience with data visualization tools — Tableau, Grafana, or equivalent — for producing operational dashboards and business reporting
Python scripting experience for data extraction, automation, or investigation workflows
Familiarity with big data, distributed systems, or cloud platforms — exposure to technologies such as Kafka, Elasticsearch, Druid, AWS, or GCP; a basic understanding of how data moves and is stored at scale is sufficient
Demonstrated use of AI tools in day-to-day work — using LLMs, AI-assisted development, or automation tools to improve the quality and speed of your output; comfort with AI as a working practice, not just an awareness of it. Experience with AI agent design or agentic workflow patterns is a significant advantage — this team is building operational practices where intelligent automation is a first-class capability
Exposure to or experience supporting API integrations and MCP (Model Context Protocol) implementations — familiarity with how modern services and AI tooling communicate at an integration level is increasingly relevant to how this platform evolves
BS or MS in Computer Science, Information Systems, Data Science, or a related discipline; equivalent professional experience will be fully considered