People Analytics Full Stack Developer

At Apple, our greatest resource is our people.

The People

Analytics team builds the\\ndata products that help Apple"s HR organization make decisions with evidence:\\nmeasuring how we recruit, develop, listen to and retain employees, and putting that\\ninsight in front of the teams and leaders who act on it. The work is small-team and\\nhigh-ownership - the person who models the data is the same person who ships the\\ndashboard and operates it in production.\\n\\nImagine what you could do at Apple.

This role builds and runs analytics products end to end: modeling data in Snowflake,\\ndeveloping Python web services and APIs, building dashboards that surface actionable\\ninsight, and automating deployment across Linux infrastructure. You will use agentic\\nAI coding tools such as Claude Code as a primary means of delivery, running parallel\\nsessions to design, build, test and ship - while holding the standards that generated\\ncode does not: sound architecture, data security, and catching the query that runs\\nwithout error and returns the wrong number.

Design, develop and deploy reports, dashboards and analytics across the employee lifecycle, enabling data-driven decisions for business partners and leadership.\\nBuild and optimize data models, schemas and views in Snowflake and relational databases to support reliable, high-quality analytics products.\\nDevelop and maintain Python backends, APIs and web frontends that power internal people tools and employee-facing applications.\\nBuild and operate ETL and data-refresh pipelines between Snowflake and operational databases, including scheduling, incremental refresh, caching and data-integrity validation.\\nAutomate build, containerization, deployment and configuration management across Linux-based infrastructure.\\nDeliver engineering work with agentic AI coding tools as the primary development method: scoping and decomposing tasks so several sessions can run in parallel, then reviewing and correcting the generated code before it ships.\\nEstablish and own metric definitions: determine how each measure is calculated, keep the same metric reporting identical wherever it appears, and validate figures against source data before release.\\nMaintain the technical documentation and codebase context that keep a large reporting estate workable, for colleagues and for AI tooling alike.\\nRe-engineer existing analytics and reporting systems to improve simplicity, standardization and security, alongside delivering new features.\\nPartner with People Analytics colleagues and internal technology teams to deliver analytics solutions.\\nResponding to senior business leaders directly on analytical questions, providing data insights and recommendations to support decision making.

Deep SQL and Snowflake experience: designing schemas, optimizing queries, and building ETL pipelines, including incremental refresh and caching strategies.\\nPython experience spanning backend web services, APIs, and data-processing automation.\\nHands-on Linux experience operating servers independently: working over SSH, running long-lived services behind a reverse proxy, and diagnosing problems with processes, networking, file systems, and performance.\\nContainer experience covering image build and deployment, as well as troubleshooting networking, storage, and runtime issues.\\nDaily production experience with agentic AI coding tools (such as Claude Code), including running parallel sessions and reviewing generated code to identify edge cases, incorrect output, and unsound patterns before shipping.\\nA track record of confirming data and system behavior by measuring against the live system rather than inferring it from documentation, naming conventions, or generated explanations.\\nExperience developing and maintaining analytics products, reports, and dashboards, including dashboard visualization development.\\nExperience handling employee data or other sensitive personal data under row-level security and data-access restrictions, with a strong understanding of legal data privacy responsibilities, duty of care, and accountability.\\nProven autonomy: experience owning delivery end-to-end with minimal direction, choosing the approach, and making implementation decisions independently.\\nExperience delivering to competing deadlines and shifting priorities without loss of data accuracy, while proactively setting expectations with stakeholders on scope and timing.\\nAbility to partner effectively with colleagues and partners across different global regions.\\nAbility to operate at a senior leader/executive level within the organization, providing data clarity and actionable insights.

Bachelor"s or Master"s degree in Computer Science, Information Management Systems, Data Science, Software Engineering or a related field; or equivalent professional experience.\\nFamiliarity with Python web frameworks such as Flask or FastAPI.\\nExperience with Python data processing libraries such as NumPy and pandas, and awareness of data science and statistical analysis techniques.\\nExperience building or operating services that make internal systems available to AI tooling, such as Model Context Protocol (MCP) servers.\\nExperience delivering on a shared data platform where pipeline changes are centrally owned: scoping a minimal change, evidencing it, and sequencing configuration and code releases.\\nExperience agreeing on metric definitions with business partners and holding those definitions consistent across multiple reporting surfaces.\\nExperience working directly with senior business leaders: taking requirements first-hand, presenting data and findings, explaining caveats clearly to non-technical partners, and responding when the numbers are challenged.