Apple
Senior Data Quality Platform Engineer
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! In this role, you will lead the development and implementation of cloud-based data applications with a focus on big data, data quality, governance, and machine learning. You will collaborate closely with cross-functional teams to gather data requirements, design scalable solutions, and ensure the accuracy, integrity, and availability of MSI data. The ideal candidate will bring a deep understanding of data engineering best practices, cloud-native architectures, and ML platform development. Description
Define and drive the roadmap for scalable data processing, data quality systems, and GenAI-focused data platform capabilities.
Architect, develop, and maintain critical data pipelines, data lakes, and model serving infrastructure with a focus on reliability, scalability, and performance.
Design and implement scalable, cloud-native data architectures with a strong emphasis on data quality, integrity, and governance.
Collaborate with data scientists, product teams, and platform engineers to build reusable, production-grade Data Quality and ML/GenAI workflows.
Continuously evaluate emerging technologies to improve data and ML infrastructure. Minimum Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
8+ years of experience in software or data engineering, with 2+ years in a technical leadership or management role is a plus. Preferred Qualifications
Proven software development, debugging, and problem-solving skills with proficiency in one or more languages: Python, Java, or Scala, Go.
Deep expertise in Big Data technologies such as Apache Spark, Kafka, Hive, Iceberg, Trino, Airflow or Flink.
Solid understanding of cloud platforms, preferably AWS, and experience building cloud-native systems.
Strong experience with modern data warehouse solutions like Apache Pinot, Snowflake, or Druid.
Hands-on experience with containerization and orchestration tools such as Kubernetes, Docker, and Helm.
Familiarity with machine learning workflows, including model training and deployment using tools like MLflow, Kubeflow, or Airflow, is a plus.
Exposure to front-end or UI technologies is a plus.
Strong people management and cross-functional collaboration skills. Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.
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! In this role, you will lead the development and implementation of cloud-based data applications with a focus on big data, data quality, governance, and machine learning. You will collaborate closely with cross-functional teams to gather data requirements, design scalable solutions, and ensure the accuracy, integrity, and availability of MSI data. The ideal candidate will bring a deep understanding of data engineering best practices, cloud-native architectures, and ML platform development. Description
Define and drive the roadmap for scalable data processing, data quality systems, and GenAI-focused data platform capabilities.
Architect, develop, and maintain critical data pipelines, data lakes, and model serving infrastructure with a focus on reliability, scalability, and performance.
Design and implement scalable, cloud-native data architectures with a strong emphasis on data quality, integrity, and governance.
Collaborate with data scientists, product teams, and platform engineers to build reusable, production-grade Data Quality and ML/GenAI workflows.
Continuously evaluate emerging technologies to improve data and ML infrastructure. Minimum Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
8+ years of experience in software or data engineering, with 2+ years in a technical leadership or management role is a plus. Preferred Qualifications
Proven software development, debugging, and problem-solving skills with proficiency in one or more languages: Python, Java, or Scala, Go.
Deep expertise in Big Data technologies such as Apache Spark, Kafka, Hive, Iceberg, Trino, Airflow or Flink.
Solid understanding of cloud platforms, preferably AWS, and experience building cloud-native systems.
Strong experience with modern data warehouse solutions like Apache Pinot, Snowflake, or Druid.
Hands-on experience with containerization and orchestration tools such as Kubernetes, Docker, and Helm.
Familiarity with machine learning workflows, including model training and deployment using tools like MLflow, Kubeflow, or Airflow, is a plus.
Exposure to front-end or UI technologies is a plus.
Strong people management and cross-functional collaboration skills. Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.