[Hiring] Senior QA Engineer @Entrada AI

Role Description

This is not a traditional QA role. You will be embedded directly into the client's Data Pipeline team (Staff Augmentation model), working toward a critical July 2026 product launch.

What You’ll Be Testing:

• API Layer: Load and stress testing of customer-facing Data Sharing APIs and data access endpoints.
• Authentication Flows: Throughput and concurrency testing of multi-tenant authentication and access control systems.
• Data Pipelines: Performance validation of data ingestion and delivery pipelines under enterprise-scale load.
• Data Isolation: Stress testing tenant data segregation logic to validate correctness and security under heavy concurrent load.

Qualifications

• 5+ years in QA engineering with a heavy focus on performance testing.
• Hands-on expertise with tools like JMeter, Gatling, k6, or equivalent.
• Deep experience testing REST APIs at scale (this is a backend-centric role, not UI/functional).
• Experience testing Databricks or Spark pipelines.
• Familiarity with cloud data platforms (e.g., Databricks, AWS) – you need to understand the architecture of data platforms.
• Multi-tenant SaaS experience – understanding of data isolation, auth flows, and concurrent user scenarios.
• Strong scripting skills for automation (Python preferred).
• Fluent English – required for direct collaboration with an international engineering team.

Requirements

• Background in FinTech or financial data platforms (Nice to Have).
• Proven track record of building performance testing frameworks from scratch (Nice to Have).

Benefits

• Competitive Salary: 140-160/h
• Start: 07.04.2026
• Stable Employment: Contract signed with our Polish entity (Entrada AI Poland).
• 100% Remote: Full flexibility to work from anywhere in Poland.
• Apple Hardware: Macbook Air M4 15" provided.
• Referral Bonus: Bonus for bringing other top-tier engineers to the team.
• Professional Growth: Databricks certification cost coverage.
• Opportunity to present at industry conferences (building your personal brand).
• Direct collaboration with Databricks MVPs and product teams.