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)