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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
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Spectraforce Technologies
May 14, 2026