Data Engineer

A globally leading consumer device company headquartered in Cupertino, CA is seeking a Data Engineer with strong data pipeline development skills and hands-on experience managing containerized workflows in Kubernetes and Docker. This role combines traditional data engineering responsibilities with infrastructure-focused work to support deployment, monitoring, and automation of data services.

Responsibilities:

•    Build and maintain scalable ELT pipelines using SQL and Python
•    Deploy, manage, and monitor containerized data workflows in Kubernetes and Docker
•    Collaborate cross-functionally to deliver reliable and well-documented data solutions
•    Implement automation and monitoring to improve system performance and reliability
•    Support urgent reporting requests and ad-hoc data analysis needs

Key Requirements:

•    2–5 years of experience in Data Engineering, Software Engineering, or Analytics
•    Strong SQL and Python skills with comfort working in Bash/Shell
•    Hands-on experience with Spark, Airflow, Snowflake, DBT, and AWS S3
•    Strong Kubernetes and Docker experience, including deploying, managing, and troubleshooting workflows
•    Familiarity with DevOps practices including CI/CD, monitoring, and automation (AWS preferred)
•    Ability to bridge both data engineering and infrastructure responsibilities
•    Solid understanding of data modeling, warehousing, and big data ecosystems
•    MS or equivalent experience preferred


Type: Contract
Duration: 12 months with extension
Work Location: Cupertino, CA (hybrid)
Pay range: $52.00 - $67.00 ph (DOE)