Camera Hardware Data Engineer

Cupertino, CA, US • Posted 3 hours ago • Updated 3 hours ago
Full Time
On-site
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Photography
  • Reporting
  • Machine Learning (ML)
  • Generative Artificial Intelligence (AI)
  • Workflow
  • Hardware QA
  • Manufacturing Operations
  • Computer Hardware
  • Analytical Skill
  • Collaboration
  • Computer Science
  • Data Engineering
  • Data Science
  • Mathematics
  • Data Analysis
  • Snow Flake Schema
  • Databricks
  • Apache Spark
  • Data Modeling
  • Data Governance
  • Artificial Intelligence
  • Microsoft Certified Professional
  • Servers
  • Orchestration
  • Python
  • PostgreSQL
  • Relational Databases
  • Redis
  • MongoDB
  • Kubernetes
  • Cloud Computing

Summary

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
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90733111
  • Position Id: a10f6ceee2484e215a90775bbb73810f
  • Posted 3 hours ago
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