Summary: Join a dynamic Quality Engineering team to develop and refine automated testing frameworks for essential trading systems, ensuring top-tier performance and reliability. Highlights: 1. Develop and support automated Python QA frameworks for trading systems 2. Optimize CI/CD pipelines and troubleshoot latency-sensitive systems 3. Contribute to testing strategies for GenAI-based services **About the Role** Join a dynamic Quality Engineering team to develop and refine automated testing frameworks for essential trading systems. You'll focus on platforms managing high\-throughput, low\-latency operations—such as algorithmic trading, order management, and market data handling—guaranteeing top\-tier performance and reliability. ***Lisbon (hybrid setup)*** **Primary Responsibilities** * Develop, implement, and support automated Python quality assurance frameworks for application and data testing. * Develop and execute automated tests for big data processing pipelines, ETL/ELT processes, and data warehouse environments, ensuring data integrity, completeness, and consistency at scale. * Perform large\-scale data validation, reconciliation, and quality control using SQL and Python on large data sets. * Improve end\-to\-end (F2B) testing using BDD frameworks for customer onboarding, regression testing, and new product launches. * Collaborate with developers, data engineers, traders, and stakeholders to refine requirements and improve software and data quality. * Optimizing CI/CD pipelines (Jenkins/TeamCity, Ansible) for seamless testing and deployment. * Troubleshooting latency\-sensitive systems and ensuring reliability in a high\-frequency trading environment. * Contributing to testing strategies for GenAI\-based services and applications working with large volumes of data. **Requirements** * 5\+ years of experience in test automation using Python as the primary language. * Proven experience in big data testing: validating data pipelines, ETL processes, data warehouses (DWH), or enterprise\-scale data lakes. * Excellent SQL skills for validating, reconciling, and analyzing data in large datasets. * Deep knowledge of the software development life cycle (SDLC), testing methodologies, and test automation best practices. * Experience with Linux (command line, scripting, system diagnostics). * Experience with big data technologies (Spark, Hadoop, Kafka, Airflow, dbt). * Upper\-intermediate English proficiency (written and spoken) **We offer:** * Hybrid work model (50/50 in the Lisbon office). * Global experience – collaboration with teams in the US, Europe, and Asia. * Career growth – mentoring, training, and clear paths from QA to Python development. * Competitive benefits – health insurance, wellness, and more. Job Types: Full\-time, Part\-time, Temporary, Contract Pay: From 65,000\.00€ per year Work Location: In person