Ecosystem QA Lead: Cross-Product Quality Champion

JetBrains; Belgrade (MT); Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Strong base salary

Flexible work schedule

Relocation support

Meals and snacks

Health & wellness

Learning & development

Internal events

Job summary

JetBrains is seeking a QA Lead to own quality across multi-component products like DataGrip within our IDE ecosystem. You will map behaviors, investigate hard-to-reproduce issues, and influence release quality across teams.

You’ll lead testing priorities, refine strategies, and guide teams through complex, distributed systems using logs and monitoring data to improve reliability and speed of delivery.

Qualifications

• Experience leading QA activities and shaping test strategies for multiple products and release cycles.
• Hands-on experience with automated tests and navigating CI/CD environments.
• Practical knowledge of relational databases and SQL.
• Familiarity with reading and debugging Java or Kotlin code to troubleshoot embedded issues.

Responsibilities

• Lead QA activities, set priorities, and coordinate testing across teams.
• Investigate cross-component issues to identify root causes.
• Analyze logs, test results, and user reports to detect quality patterns.
• Define test strategies and apply risk-based testing for safe releases.
• Collaborate with developers and product teams to define expected behavior when specs are missing.
• Improve QA processes and guide the team toward reliable releases.

Skills

QA leadership

Test strategy

Analytical thinking

Cross-team coordination

CI/CD familiarity

Troubleshooting logs

Docker

Kubernetes

TeamCity

SQL

Java

Kotlin

Tools

TeamCity

Docker

Kubernetes

SQL

Java

Kotlin

Job description

JetBrains is seeking a QA Lead to own quality across multi-component products like DataGrip within our IDE ecosystem. You will map behaviors, investigate hard-to-reproduce issues, and influence release quality across teams.

You’ll lead testing priorities, refine strategies, and guide teams through complex, distributed systems using logs and monitoring data to improve reliability and speed of delivery.