Reliability Engineer - Data

Apple Inc

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: Austin, TX
Posted: 13 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $208k

$138k most similar roles pay here $277k

This listing doesn't post a salary. Most similar roles pay $172,500–$243,600.

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 · Reliability Engineer - Data

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As a Reliability Engineer - Data, Apple Ads, you will join the team responsible for managing cloud-based systems and infrastructure that store, process, transform, and analyze large datasets. You will design, build, and manage large-scale distributed data systems on AWS using services like EMR, EKS, MSK, and Iceberg while developing internal tooling and automation frameworks to improve reliability, cost-efficiency, and observability. The role involves collaborating with cross-functional engineering teams in advertising, machine learning, and data platforms to troubleshoot complex issues and drive production excellence. You will utilize technologies including Apache Spark, Flink, Kafka, Kubernetes, and Helm for Infrastructure as Code. Your work focuses on the technical challenge of maintaining a multi-cloud ecosystem while leveraging ML and GenAI capabilities to improve infrastructure efficiency for systems supporting advertising across various Apple Services.

Skills

AWS Kubernetes Apache Spark Flink Kafka Iceberg EMR EKS MSK Python Java Scala Kotlin Helm Infrastructure as Code GenAI Machine Learning Distributed Systems

What you'll do

Design, build, and manage large-scale distributed data systems on AWS using services like EMR, EKS, and MSK.
Develop internal tooling and automation frameworks to improve infrastructure reliability, cost-efficiency, and observability.
Eliminate manual toil by implementing automated processes and scalable deployment patterns.
Manage Infrastructure as Code (IaC) using Helm and CRDs to ensure secure and repeatable deployments.
Troubleshoot complex issues within large-scale distributed systems to maintain production excellence.
Optimize performance and costs for high-volume data processing and storage systems.
Drive the adoption of new technologies and influence the design of multi-cloud infrastructure.

What we're looking for

2+ years of experience in Infrastructure Engineering focusing on building, scaling, and operating cloud-based distributed data systems.
Proven expertise running cloud infrastructure built on managed services from providers like AWS.
Strong technical grasp and experience with open-source technologies for large-scale data processing like Spark, Flink, Kafka, or Iceberg.
Strong expertise and experience with container orchestration systems such as Kubernetes.
Experience leveraging ML and GenAI capabilities to improve infrastructure and operational efficiency.
Proficiency in object-oriented, functional, or procedural programming languages, preferably Java, Scala, Kotlin, or Python.
Experience designing and managing Infrastructure as Code using Helm and CRD for scalable deployments.
Track record of driving automation, cost optimization, and performance tuning for large-scale distributed systems.

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