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We are looking for a skilled QA Automation Engineer (backend oriented) to join our Parking domain. You will play an important role in ensuring the quality of mission-critical systems that serve millions of users daily.
The majority of the role is automated testing combing AI Skills but combines manual as well.
This is a great opportunity for somebody who want to enhance infrastructures, develop in engineering and great best practices and handle scaled distributed systems based on AWS.
Responsibilities
Design and develop automated tests end to end for new and existing features, execute mainly Backend API tests, including automation for backend services.
Apply AI tools (e.g., Cursor, Claude Code) in day-to-day work to generate code, build automation, and continuously improve testing workflows.
Write and maintain detailed test cases and documentation.
Identify, record, and track software defects and issues, ensuring timely resolution.
Work with tools such as Qase.
Collaborate with cross-functional teams to understand product requirements and design effective testing strategies.

We are seeking a QA Engineer with a strong passion for data quality, performance, and scale to join our Data Platform team.
This role is ideal for a QA professional who enjoys working close to complex data systems, understands large-scale pipelines, and wants to play a key role in shaping the automation and quality strategy of a data engineering organization.
You will act as the primary quality owner for high-volume, mission-critical data platforms, working closely with data engineers, backend developers, and platform teams.
What Youll Do:
Data Quality & Validation:
Design and execute data validation strategies for large-scale batch and streaming pipelines
Ensure data correctness, completeness, freshness, and consistency across the data lake
Define and automate checks for schema changes, data drift, and data quality regressions
Performance & Scalability Testing:
Plan and execute performance and scalability tests for data pipelines and processing jobs
Identify bottlenecks across ingestion, transformation, and querying layers
Partner with engineers to validate performance improvements and prevent regressions
Automation & Infrastructure:
Develop and maintain the data teams QA automation infrastructure
Build reusable testing frameworks and tools tailored for large datasets and pipelines
Integrate automated tests into CI/CD pipelines and production monitoring workflows
Collaboration & Ownership:
Work closely with data engineers, backend developers, and platform engineers throughout the development lifecycle
Act as the sole QA owner within a cross-functional team, driving quality without becoming a bottleneck
Participate in design discussions to ensure testability and observability are built in from the start
Quality Mindset & Communication:
Champion a quality-first culture within the team
Clearly communicate risks, findings, and quality metrics to technical stakeholders
Balance thoroughness with pragmatism in fast-moving, high-scale environments.