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Analytics Full Stack Developer

Job in Austin, Travis County, Texas, 78716, USA
Listing for: Apple Inc.
Full Time position
Listed on 2026-10-18
Job specializations:
  • Software Development
    Data Engineering, Python, AI Engineer (Applied/Software), Software Engineer
Salary/Wage Range or Industry Benchmark: 140000 - 180000 USD Yearly USD 140000.00 180000.00 YEAR
Job Description & How to Apply Below

Austin, Texas, United States Corporate Functions

At Apple, our greatest resource is our people. The People Analytics team builds thedata products that help Apple's HR organization make decisions with evidence:measuring how we recruit, develop, listen to and retain employees, and putting that insight in front of the teams and leaders who act on it. The work is small-team andhigh-ownership - the person who models the data is the same person who ships the dashboard and operates it in production.

Description

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

Responsibilities
  • Design, develop and deploy reports, dashboards and analytics across the employee
  • lifecycle, enabling data-driven decisions for business partners and leadership.
  • Build and optimize data models, schemas and views in Snowflake and relational
  • databases to support reliable, high-quality analytics products.
  • Develop and maintain Python backends, APIs and web frontends that power internal
  • people tools and employee-facing applications.
  • Build and operate ETL and data-refresh pipelines between Snowflake and operational
  • databases, including scheduling, incremental refresh, caching and data-integrity
  • validation.
  • Automate build, containerization, deployment and configuration management across
  • Linux-based infrastructure.
  • Deliver 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.
  • Establish and own metric definitions: determine how each measure is calculated,
  • keep the same metric reporting identically wherever it appears, and validate
  • figures against source data before release.
  • Maintain the technical documentation and codebase context that keep a large
  • reporting estate workable, for colleagues and for AI tooling alike.
  • Re-engineer existing analytics and reporting systems to improve simplicity,
  • standardization and security, alongside delivering new features.
  • Partner with People Analytics colleagues and internal technology teams to deliver
  • analytics solutions.
  • This role works with colleagues in other regions, so occasional meetings outside
  • standard working hours should be expected. Regular travel is not required.
Minimum Qualifications
  • Bachelor's degree in Computer Science, Information Management Systems, Data Science,
  • Software Engineering, or a related field.
  • 7+ years of experience developing and maintaining analytics products, reports and
  • Deep SQL and Snowflake experience: designing schemas, optimizing queries, and
  • building ETL pipelines including incremental refresh and caching strategies.
  • Python experience spanning backend web services, APIs, and data-processing
  • automation.
  • Hands-on Linux experience operating servers unaided: working over SSH, running
  • long-lived services behind a reverse proxy, and diagnosing problems with processes,
  • networking, file systems and performance.
  • Container experience covering image build and deployment, and troubleshooting
  • networking, storage and runtime issues.
  • Daily 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 it ships.
  • A track record…
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