Senior Data Platform Support Engineer – Kubernetes & Cloud

starburst; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Equity

Flexible PTO

Job summary

Starburst is seeking a skilled enterprise technical support engineer to help customers optimize data-platform deployments. You will troubleshoot incidents, guide upgrades, and perform proactive check-ins while contributing to docs and knowledge sharing.

You will collaborate with cross-functional teams, conduct regular technical reviews, and ensure best practices across Hadoop, Spark, containers, and cloud environments. Travel ~25% required; Pacific Time zone alignment provided.

Qualifications

• Five+ years in technical support.
• Three+ years with big-data systems, containers, Kubernetes, and cloud tech.
• Knowledge of Hadoop, data lakes or Spark; Docker; Kubernetes; AWS/Azure/GCP.
• Familiar with Linux, SQL and DB concepts; LDAP or OAuth 2.0.
• SSL/TLS familiarity; scripting languages like SQL, Java, Python, Bash.
• Travel ~25% as needed.

Responsibilities

• Investigate questions and incidents, reproduce problems, identify root causes, and communicate solutions via ticketing.
• Support long-term-version upgrades and coordinate unsupported versions with account teams.
• Hold regular technical reviews with customer groups on cases, product issues, best practices, and status.
• File product defect reports and feature requests with internal teams.
• Contribute to reference docs, advise content teams, and lead knowledge sharing or peer training.
• Help deliver departmental initiatives and address cross-functional obstacles.

Skills

Technical support

Big-data systems

Containers

Cloud technologies

Linux & SQL basics

Tools

Docker

Kubernetes

AWS/Azure/GCP

SQL

Job description

Starburst is seeking a skilled enterprise technical support engineer to help customers optimize data-platform deployments. You will troubleshoot incidents, guide upgrades, and perform proactive check-ins while contributing to docs and knowledge sharing.

You will collaborate with cross-functional teams, conduct regular technical reviews, and ensure best practices across Hadoop, Spark, containers, and cloud environments. Travel ~25% required; Pacific Time zone alignment provided.