MSI Data Engineer

Santa Clara Valley (Cupertino), California, United States
Software and Services


Weekly Hours: 40
Role Number:200198316
Location: Cupertino, CA Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. 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 within Apple’s Operations team. This data is stored and used during the entire product's lifecycle- from prototypes to mass production through warranty support for customers.Our environment fosters product innovation, rapid iteration, and a liberating amount of autonomy. As an expert in developing software to manage large, dynamic data sets, you'll be building platform for data ingestion, cleaning, transformation and evaluation to support a rapidly scaling organization.

Key Qualifications

  • 5+ years of professional experience with Big Data systems, pipelines and data processing
  • Hands on experience Big Data, data ingestion, data processing using Spark, Spark Streaming, Flink, HIVE, Kafka, Hadoop, HDFS, S3
  • Hands-on experience with design and development with NoSQL technologies Cassandra, HBase or similar scalable Key valueStores and time series data stores like Druid, influx or similar
  • Understanding on various distributed file formats such as Apache AVRO, Apache Parquet and common methods in data transformation
  • Confirmed understanding of design and development of large scale, high throughput and low latency applications is a plus
  • Understanding and experience with Micro Services is desired
  • Excellent problem solving and programming skills
  • Experience with containerization technologies like Kubernetes, Docker, Mesos, Marathon is desirable
  • Experience with CI/CD, debugging and monitoring applications and big data jobs is desirable


Do you love the idea of solving a new business or technical problem every other day with a wide range of technologies? Join our team and be a part of a fast-paced, iterative environment with many exciting responsibilities! We are looking for highly motivated, detail oriented, technically savvy, high-energy professionals who like to re-define large data platforms. Responsibilities: Develop solutions to answer complex analytical and real-time operational questions Help to design, architect and build the data platform using a variety of Big Data technologies Design and develop applications involving data processing, hygiene, augmentation and transformation for distributed systems Identify Data Validation rules and alerts based on data publishing specifications for data integrity and anomaly detection Innovate by exploring, recommending, benchmarking, and implementing data centric platform technologies Ensure operational and business metric health by monitoring production decision points Provide hardware architectural guidance, estimate cluster capacity, and create roadmaps for Hadoop cluster deployment

Education & Experience

BS, MS, or PhD in Computer Science, Computer Engineering, or equivalent practical experience. Apple is an Equal Opportunity Employer that is committed to inclusion and diversity. We also take affirmative action to offer employment and advancement opportunities to all applicants, including minorities, women, protected veterans, and individuals with disabilities. Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants.

Additional Requirements