Finance Data Engineer

Apple Inc

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: Austin, TX
Posted: 93 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $169k

$117k most similar roles pay here $221k

This listing doesn't post a salary. Most similar roles pay $126,800–$211,200.

Based on 240 similar postings.

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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 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Finance Data Engineer

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The Finance Data Engineer joins the Apple Finance team as a technical expert responsible for creating data interfaces, pipelines, and codebases that drive innovative data products. Working cross-functionally with business users, data scientists, and engineers, you will identify, capture, load, and format data from internal systems and external sources into enterprise warehouse and lakehouse environments. You will develop, test, deploy, and monitor data pipelines while translating finance use cases into requirements for RAG, agents, and LLM workflows. The role requires proficiency in Python, shell, and SQL, along with experience in Snowflake, S3, Jenkins, Git, AWS, and Kubernetes. Key responsibilities include implementing encryption policies for sensitive data, managing streaming interfaces via RESTful APIs, and ensuring high data quality to solve complex business questions within the finance domain.

Skills

Python SQL Shell Snowflake S3 AWS Kubernetes CI/CD Git Jenkins Lakehouse RAG LLM Data Pipelines Encryption Version Control

What you'll do

Create data interfaces, pipelines, and codebases to drive innovative products for Apple Finance.
Collect, load, and format data from external sources, internal systems, and the enterprise data warehouse.
Develop, test, deploy, monitor, and troubleshoot data pipelines and feature-ready datasets.
Translate finance use cases into technical requirements, schemas, and retrieval patterns for LLM workflows.
Implement end-to-end encryption and decryption policies for sensitive data pipelines and semantic views.
Build automated data services via RESTful interfaces.
Identify and integrate emerging technologies to enhance data capabilities and techniques.

What we're looking for

Undergraduate degree in Computer Science, MIS, Engineering, Mathematics, or another quantitative discipline.
5+ years of relevant Data Engineering experience.
Proficiency in Python, shell, and SQL programming.
Experience with database design and architecture in cloud data warehouses (Snowflake) and lakehouse environments (S3).
Ability to implement end-to-end encryption and decryption policies for sensitive data pipelines.
Experience with the data development lifecycle including CI/CD and version control tools like Jenkins and Git.
Exposure to cloud storage and orchestration tooling such as AWS and Kubernetes.
Experience with streaming interfaces, RESTful APIs, and finance or accounting processes is preferred.