PART DataOps Engineer

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$118,500–$197,500 / yr
Posted
today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $166k
This role $158k
$108k most similar roles pay here $215k

This role pays less than 59% of similar roles. Most pay $126,800–$205,000 — the shaded band above. At the midpoint, this role pays about $158k versus about $166k for comparable roles.

Based on 239 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1780 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1441 roles with salary data.

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At a glance

TL;DR · PART DataOps Engineer

Apple’s PART Data Operations group seeks a senior Data Engineer to join the Next-Gen Workflow team. This role involves designing and building data applications using Python frameworks like Streamlit to streamline financial analysis and reporting for Apple’s Finance analysts. The ideal candidate will independently manage complex projects from discovery through deployment, integrating AI technologies such as LLMs into both internal practices and products used by stakeholders. Key responsibilities include developing lightweight web interfaces, connecting applications to diverse data sources, and coaching analysts on AI integration. Expert proficiency in Python, experience with relational databases and modern data lakes, and strong software engineering fundamentals are essential. Preferred qualifications include hands-on AI/LLM tooling experience, expertise in FastAPI or similar frameworks, and a background in Finance or FP&A.

What you'll do

  • Own complex data projects from discovery to long-term maintenance.
  • Design and deploy Streamlit-based applications for financial analysis.
  • Lead the team’s adoption of AI in both engineering practice and products.
  • Coach financial analysts on applying AI in their workflows effectively.
  • Write clean Python code, establish patterns, and mentor other engineers.

What we're looking for

  • 6+ years of data engineering or software development with a track record of shipping production applications end-to-end.
  • Expert proficiency in Python and hands-on experience building and deploying web applications using Streamlit.
  • Strong experience with relational databases and modern data lake environments.
  • Solid software engineering fundamentals including Git, code review, testing, CI/CD, and observability practices.
  • BS degree in Computer Science, Data Science, Engineering, or a related field.

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