Reliability Engineer - Data

Apple Inc

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: Austin, TX
Posted: 10 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 infrastructure supporting advertising across various services. You will design, build, and manage large-scale distributed data systems and cloud-based infrastructure used to store, process, transform, and analyze massive datasets. Your daily work involves developing internal tooling and automation frameworks to improve reliability, cost-efficiency, and observability while eliminating toil through scalable deployment patterns. You will utilize technologies including AWS services like EMR, EKS, MSK, and Iceberg, alongside open-source tools such as Apache Spark, Flink, and Kafka. The role requires expertise in Kubernetes, Infrastructure as Code with Helm and CRD, and programming in Java, Scala, Kotlin, or Python. You will also leverage ML and GenAI capabilities to enhance operational efficiency within a multi-cloud environment.

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 for advertising and machine learning platforms.
Optimize performance and costs for high-volume data processing and storage systems.
Drive the adoption of new technologies and contribute to strategic multi-cloud infrastructure decisions.

What we're looking for

At least 2 years of experience in Infrastructure Engineering focused 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 such as Apache Spark, Flink, Kafka, or Iceberg.
Strong expertise and experience with container orchestration systems like 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 data systems.

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