Proactively drive QA topics across the organization, ensuring quality considerations are embedded early in requirements definition, architecture discussions, and design decisions * Take ownership of quality governance, defining and refining QA methodologies, standards, and best practices across frontend, backend, and data components * Ensure that backend services and data pipelines follow robust validation and monitoring practices * Knowledge of data analytics tools (e.g., Power BI) for test result visualization and tracking * Knowledge of data science and machine learning * Knowldge of big data pipeline technologies (e.g. Trino, Flink, Apache Kafka) * Knowledge of big data and IoT applications in the context of heavy machines * Knowledge of hardware (related in particular to data logging and edge computing) and related embedded software
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