Staff Data Engineer

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Austin, TX
Posted
28 days ago
Freshness
Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $190k
$144k most similar roles pay here $235k

This listing doesn't post a salary. Most similar roles pay $159,875–$219,425.

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 · Staff Data Engineer

The Staff Data Engineer joins the Risk and Vulnerability Management team within Apple Services Engineering Security to lead data engineering and architecture efforts. This role focuses on building a unified security data platform that serves as a system of record for findings, a graph for ownership and blast radius, and a lakehouse for posture metrics. You will own the data model, manage pipeline contracts, and automate ownership attribution and risk enrichment. The work involves processing signals from various systems to identify and triage risks across infrastructure, platforms, and services. Required skills include expertise in Spark, Hadoop, Presto, Flink, Druid, and SQL, along with proficiency in Java, Python, or Scala. Candidates should also possess knowledge of AWS resources, network protocols, and distributed data service architecture to solve complex problems within a matrixed organization.

What does a Data Engineer earn?

Median $183138 from 214 postings across 58 companies.

See salary data

What you'll do

  • Design and own the data model and pipeline contracts for a centralized security data platform.
  • Build and manage large-scale distributed data pipelines using Spark, Flink, or similar technologies.
  • Transition prototype data pipelines into production systems that the business relies on daily.
  • Automate ownership attribution and risk enrichment to replace manual data processing tasks.
  • Develop a system of record for security findings and a graph for asset ownership.
  • Create a lakehouse architecture to provide posture metrics and analytics for leadership.
  • Establish technical direction and strategy across a large, matrixed engineering organization.

What we're looking for

  • 15+ years of experience working with Spark and other distributed data technologies like Hadoop, Presto, Flink, or Druid.
  • Proficiency in at least one of Java, Python, or Scala.
  • Deep expertise in Data Principles, Data Architecture, Data Modeling, and strong SQL skills.
  • Experience working in a complex, matrixed organization with cross-functional or cross-business projects.
  • Strong communication and collaboration skills to lead high-level discussions on technology strategy.
  • Conceptual familiarity with AWS cloud resources, the OSI model, and full technology stack primitives.
  • Experience building stream-processing applications using Apache Flink, Spark-Streaming, Apache Storm, Kafka Streams, or others (preferred).
  • Experience with Search systems, NoSQL datastores, or building distributed, high-volume data services (preferred).

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