Data Quality Engineer We are looking for a Data Quality Engineer to join our team and contribute to data governance processes, quality assurance, and the development of robust data platforms that support reliable data-driven decision-making. Responsibilities Play a role in the data governance processes, including data preparation, generation, data obfuscation, data integration, data slicing and data quality control Prepare test data sets, perform data profiling and benchmarking Perform testing of data ingestion pipelines, ETLs, APIs and integrations Take part in designing and maintaining data platforms, data quality automation framework Maintain QA environments, contribute to the CI/CD process establishment Support customer inquiries on data quality issues and data consumption Requirements 1+ years of hands-on engineering experience and practice in Data Management, Data Quality verification/Data Governance, Data Integration Understanding of data ingestion pipelines, Data Lakes, ETL testing, DWH basics Knowledge of CI/CD principles and best practices in data processing Proficiency in SQL Knowledge of Python (or other scripting languages) Experience with one of the major cloud providers: AWS, Azure or GCP Understanding of test automation Experience in Data analysis & requirements validation Experience in Test Case design and bug reporting Analytical approach to problem solving; excellent interpersonal and communication skills English proficiency at B2 level or higher Nice to have Knowledge of a few data processing technologies, e.g., Spark, Hadoop, Kafka, ElasticSearch, Python libraries (Pandas/NumPy/...) Understanding of various ETL Tools (e.g., Databricks) Understanding of Big Data principles Familiarity with Linux and Bash scripting basics Experience in Data Visualization testing Experience in maintaining QA environments Understanding of Data project Test Strategy creation and test planning