Hardware Data Engineer - Camera

Apple delivers the most popular cameras in the world. Each product release provides breakthroughs in photography with stunning camera features that customers love. Our cameras deploy imaging complexity at the frontier of traditional camera engineering methods. Data volumes are growing to meet this need across camera simulations, performance calibrations, measurement results, and their correlations. Our team's task is to build a comprehensive aggregate data layer that enables efficient and flexible executive reporting, highly customized data applications, and powerful ML inference and analysis.

In this role, you will work closely with data scientists, hardware engineers, hardware test, and manufacturing operations teams to build scalable data pipelines and solutions. As a hardware data engineer, you must effectively collaborate to bridge the gap between business needs, analytical solutions, and engineering requirements. Additionally, proactive collaboration with other data engineering teams is essential for scaling solutions across teams.

Responsibilities
As part of the Camera Hardware Data Engineering team, you will be responsible for expanding our powerful data engineering platform and custom team tools by designing, developing, and maintaining robust data pipelines to support camera manufacturing analytics initiatives. You will work independently to design technical solutions to process massive datasets and engage with internal and external data providers and consumers to create low-friction data exchange systems. You will provide technical leadership for 3rd party development teams and mentor and provide data engineering best practices across the organization.

Minimum Qualifications
BS or higher in Computer Science, Data Engineering, Data Science, Math, or related fields. Hands-on experience using cloud data analytics platforms (i.e. Snowflake, Trino, BigQuery). Experience building data transformation pipelines using frameworks such as Data Built Tool (dbt) or Spark. Experience in data modeling and data governance techniques (i.e. Row Access Policies, role-based access control (RBAC).

Preferred Qualifications
Experience with pipeline orchestration frameworks such as Airflow. Experience using BI tools such as Tableau or app frameworks such as Streamlit or Superset to build shareable and easy-to-understand data visualizations. Experience in the use of Python frameworks like FastAPI to build cloud-native data access tools. Experience designing and building relational databases (i.e. PostgreSQL) and non-relational databases (i.e. Redis, MongoDB). Working knowledge of Kubernetes for deploying and monitoring cloud-native applications.

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.

Apple accepts applications to this posting on an ongoing basis.