Finance Data Engineer

Apple Inc

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Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$149,200–$249,000 / yr
Posted
139 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $169k
This role $199k
$112k $264k
below market most similar roles pay here above market

This role pays more than 70% of similar roles. Most pay $126,800–$211,200 — the blue band above. At the midpoint, this role pays about $199k versus about $169k for comparable roles.

Based on 240 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 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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At a glance

TL;DR · Finance Data Engineer

JOB TITLE: Finance Data Engineer The Finance Data Engineer joins the Finance team as a technical expert responsible for creating data interfaces, pipelines, and codebases that drive innovative data products. This role involves working cross-functionally with data scientists, machine learning engineers, and business partners to identify, capture, load, and format data from internal systems and external sources. Key responsibilities include developing, testing, and monitoring data pipelines and feature-ready datasets while translating finance use cases into schemas for RAG and LLM workflows. The position requires proficiency in Python, shell, and SQL, along with experience in Snowflake, S3, Jenkins, Git, AWS, and Kubernetes. The engineer will operate within enterprise data warehouse and lakehouse environments to solve complex business questions and implement encryption policies for sensitive data pipelines.

What you'll do

  • Develop, test, deploy, monitor, and troubleshoot data pipelines and feature-ready datasets.
  • Capture, collect, load, and format data from external sources, internal systems, and data warehouses.
  • Translate finance use cases into data requirements, schemas, and retrieval patterns for LLM workflows.
  • Implement end-to-end encryption and decryption policies for sensitive data pipelines and semantic views.
  • Build and maintain data interfaces and pipelines within enterprise data warehouse and lakehouse environments.
  • Implement data and automation services via RESTful interfaces.
  • Identify and review emerging technologies to enable the adoption of new techniques and tools.

What we're looking for

  • 5+ years of relevant Data Engineering experience.
  • Undergraduate degree in Computer Science, MIS, Engineering, Mathematics, or another quantitative discipline.
  • Effective Python, shell, and SQL programmer (preferred).
  • Hands-on experience with database design and architecture in cloud data warehouses (Snowflake) and lakehouse environments (s3) (preferred).
  • Ability to implement end-to-end encryption and decryption policies for sensitive data pipelines (preferred).
  • Experience with the data development lifecycle, CI/CD, and version control tools like Jenkins and Git (preferred).
  • Exposure to cloud storage and orchestration tooling such as AWS and Kubernetes (preferred).
  • Experience with streaming interfaces, RESTful APIs, and finance/accounting processes (preferred).

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