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Apple

Data Engineer (m/f/d)

Apple
Germany · Full-time · Entry

Summary

Do you love crafting elegant solutions to highly complex challenges? Do you intrinsically see the importance in every detail? As part of our Silicon Technologies group, you'll help design and manufacture our next-generation, high-performance, power-efficient processor, system-on-chip (SoC). You'll ensure Apple products and services can seamlessly and expertly handle the tasks that make them beloved by millions!

Joining this group means you'll be responsible for crafting and building the technology that fuels Apple's devices. Together, you and your team will enable our customers to do all the things they love with their devices. At Apple, innovative concepts swiftly transform into groundbreaking products, services, and customer experiences. By cultivating passion and unwavering dedication, the potential for extraordinary accomplishments becomes limitless. As a member of the Apple Silicon Technology group, you will collaborate in the design, creation, and enhancement of our data infrastructure, which underpins the productization of our semiconductors across iPhone, iPad, Mac, and numerous other devices.

We are seeking a highly skilled Data Software Engineer to design, develop, and maintain scalable data infrastructure and software systems. The ideal candidate will seamlessly bridge the gap between software engineering and data engineering, constructing robust data pipelines, analytics platforms, and data-driven applications that empower our organization to derive valuable insights from extensive datasets.

Description

Within the Productization Data Tools team, you will assume the responsibility for developing and maintaining the software systems that underpin our data operations. Your role will entail close collaboration with data scientists, analysts, and product teams to establish reliable, high-performing, and scalable data solutions. Your responsibilities will encompass designing data architectures, optimizing data processing workflows, and ensuring data quality and governance throughout our systems.

Responsibilities

  • Design and implement scalable data pipelines and processing systems
  • Parse and process text logs and STDF
  • Develop and optimize database performance and query efficiency
  • Implement data quality monitoring and validation frameworks
  • Collaborate with data scientists to productize machine learning models
  • Monitor system performance and troubleshoot data infrastructure issues

Minimum Qualifications

  • Experience in data engineering or data-focused software development
  • Experience in software development, with a specific focus on data systems
  • Proficiency in Python programming language
  • Strong problem-solving and analytical abilities
  • Degree in Computer Science, Software Engineering, or a related field)

Preferred Qualifications

  • Experience with Oracle SQL and database design principles
  • Experience with Linux operating systems
  • Proficiency in version control systems (Git)
  • Excellent communication and collaboration skills
  • Experience in semiconductor or high-tech research and development (R&D) and manufacturing environments
  • Experience with Cassandra NoSQL database
  • Familiarity with machine learning workflows and machine learning operations (MLOps) practices
  • Experience with data visualization tools and business intelligence platforms

At Apple, we’re not all the same. And that’s our greatest strength. We draw on the differences in who we are, what we’ve experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.

Key Skills

Ranked by relevance

machine learning data visualization cassandra python oracle nosql linux mlops sql
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Posted
Jan 28, 2026
Type
Full-time
Level
Entry
Location
Stuttgart
Company
Apple

Industries

Computers Electronics Manufacturing

Categories

Information Technology

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