Data Quality Assurance Engineer (Automation & Observability)

Description Fetcherr experts in deep learning, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Specializing initially in the airline industry, Fetcherr aims to revolutionize industries with dynamic AI-driven solutions. Fetcherr experts in deep learning, algo-trading, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Specializing initially in the airline industry, Fetcherr aims to revolutionize industries with dynamic AI-driven solutions.

We’re looking for a Data Quality Assurance Engineer to join our Price Optimization Department with a focus on automation, observability, and performance. In this role, you will design and implement validation frameworks in code, build automation around data quality monitoring, and contribute to the observability and performance testing of large-scale pipelines. You will collaborate closely with data engineers, scientists, and analysts to ensure our AI-driven models operate on reliable, high-quality data. The ideal candidate will be a strong Python developer with hands-on experience in data frameworks and distributed systems, combined with solid knowledge of OLAP databases and data pipeline concepts. Key responsibilities Design and implement automated validation procedures for pipelines and transformations Develop monitoring and observability tools to ensure data quality and reliability Contribute to performance testing and optimization of large-scale data systems Build and maintain reusable Python-based validation frameworks Collaborate with data engineers, scientists, and analysts to define quality metrics and integrate them into observability dashboards Investigate complex issues in distributed data systems and contribute fixes and improvements Technical requirements

Requirements You’ll Be a Great Fit if You Have… 4+ years of hands-on Python development experience in Data Quality Assurance or similar role (must) Proficiency with standard data libraries (Pandas, NumPy, etc.) (must) Strong understanding of ETL/data pipeline testing and Big Data platforms (must) SQL and OLAP databases proficiency (good plus) [ClickHouse – strong plus] Experience with orchestrators (good plus); Dagster - strong plus Experience with distributed data frameworks such as Ray Data (strong plus) Cloud experience (GCP is a strong plus) Exposure to test management or defect tracking tools (desirable) Soft requirements Ability to deliver against aggressive timelines in a very dynamic startup environment (must) Strong problem-solving mindset with a focus on building scalable and reliable automation Flexibility to adapt to changing project demands (occasional paid overtime may be required) (good plus) Knowledge of the airline industry (pricing, revenue management) (strong plus) Experience working within Agile methodologies