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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