Camera Hardware Data Engineer

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, powerful ML inference, and agentic GenAI workflows.

Description

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 camera 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.

Minimum Qualifications

BS in Computer Science, Data Engineering, Data Science, Math, or related fields
Hands-on Experience using cloud data analytics platforms (i.e. Snowflake, Databricks, or similar)
Experience building data transformation pipelines using frameworks such as Data Built Tool (dbt) or Spark
Experience in data modeling and data governance techniques

Preferred Qualifications

10 years of relevant industry experience
Experience in building and validating AI tooling such as MCP servers, automated agents, and RAG pipelines
Experience with pipeline orchestration frameworks such as Airflow
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