Data Engineer

Role: Data Engineer

Location: Cupertino, CA (Hybrid)

Duration: 12 months

Role Overview

We are 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.

Key Skills:

• SQL, Python, Bash/Shell scripting
• Spark, Airflow
• Snowflake, DBT
• AWS S3, Kubernetes
• GitHub, Docker
• DevOps, CI/CD

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

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

Education:

• MS or equivalent experience preferred