Job Description

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something.



Apple's Manufacturing Systems and Infrastructure (MSI) team is responsible for capturing, consolidating and tracking all manufacturing data for Apple's products and modules worldwide. As a Software Engineer in this team, you are an integral part of a small data-centric team driving large-scale data infrastructure and processes development, implementation, and improvement. Our organization thrives on collaborative partnerships. Join and play a key role in developing and driving the adoption of Data Mesh and data-centric micro-services.



Our tools enable teams to confidently use data to shape the next generation of product manufacturing at Apple. We seek a practitioner with experience building large-scale data platforms, analytic tools, and solutions. If you are passionate about making data easily accessible, trusted, and available across the entire business at scale, we'd love to hear from you.

Description

As a Software Engineer, you will work closely with cross-functional teams to understand business requirements, design scalable solutions, and ensure the integrity and availability of our data. The ideal candidate will have a deep understanding of cloud technologies, UI technologies, software engineering best practices, and a proven track record of successfully delivering complex projects.","responsibilities":"Design and develop software applications and API's for large scale data to enable analytics and ML use cases at Apple Product Operations

Responsible in crafting, developing and maintaining our large-scale micro services services

Build self-service analytics and ML tools to help engineering teams derive actionable metrics out of large volumes of raw data

Partner with different Ops teams, data science and engineering teams and develop platforms/apps/algorithms to answer complex questions on quality of our products

Work closely with the DevOps team and develop monitoring and alerting scripts on various web, data pipelines and jobs

Have the opportunity to learn and work on the latest technologies, lead POCs to demonstrate new ideas and influence the future direction of our technology stack

Collaborate with a diverse team of Designers, Developers, and Engineers and Translate designs and wireframes into high quality code

A self starter, forward-thinking person to consider implications of choices and communicate key decision junctures driving technical design decision-making

Preferred Qualifications

Hands-on experience with Apache Spark (PySpark), Apache Kafka, and Ray for distributed computing and streaming, Apache Airflow for workflow orchestration, and Pandas/NumPy for data manipulation

Debugging and problem-solving skills with production observability tools like CloudWatch Logs Insights and Splunk

Experience with cross-functional collaboration across all stages of product lifecycle (prototype and production)

Minimum Qualifications

Bachelors degree in computer science or equivalent field with of 6 - 12 years hands-on programming experience

Deep expertise in React and TypeScript with understanding of modern patterns (hooks, context) and Redux Toolkit for state management

Experience building RESTful APIs using Python and FastAPI, with understanding of async/await patterns and Pydantic data validation

Extensive experience with PostgreSQL using SQLAlchemy, MySQL/SingleStore, and distributed query engines like Trino for large-scale data operations

Expert-level experience deploying and managing applications on Kubernetes and AWS (EKS, S3), including Helm charts, Docker containerization, and Infrastructure as Code

Proficiency with Git/GitHub Enterprise, CI/CD pipelines, and deployment automation","internalDetails":null,"eeoContent":null