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We are looking for a Lead Data Quality Engineer to drive the data quality testing strategy across our products, collaborating with cross-functional teams to ensure data reliability, governance, and performance meet the highest standards.
Responsibilities
- Work with product, engineering and customer teams to understand requirements and implement a quality testing strategy, defining and setting up data quality metrics
- Design and implement a quality verification strategy for data products and ensure that all areas of the business perform according to the defined standards
- Define priorities, risks and attributes in the data quality testing strategy, as well as choose proper data tools
- Control and tune the data governance processes, including data preparation, generation, data obfuscation, data integration, data slicing and data quality control
- Prepare data quality environments and applications in compliance with the standards
- Design, monitor and maintain QA reports, KPIs and quality trends
- Collaborate with all teams involved in data solution development to ensure efficient task execution for achieving results
- Adhere to and promote quality standards
Requirements
- 5+ years of hands-on engineering experience and practice in Data Management, Data Quality verification/Data Governance and Data Integration
- Understanding of data pipelines, data lakes and ETL testing
- Experience in CI/CD principles and best practices in data processing
- Knowledge of SQL
- Proficiency in Python or other scripting languages
- Experience with one of the major cloud providers: AWS, Azure or GCP
- Experience in building up a test automation framework and maintaining QA environments
- Experience in data analysis and requirements validation
- Concrete experience in Data project Test Strategy creation, Test Planning, Test Case design and test result reporting
- Skills in infrastructure troubleshooting, support in performance tuning and optimization, and bottleneck problem analysis
- Experience in leading a team and in direct customer communications
- Analytical approach to problem solving, excellent interpersonal and communication skills, and English proficiency
Nice to have
- Familiarity with a few data processing technologies, e.g., Spark, Hadoop, Kafka, Elasticsearch, Python libraries (Pandas/NumPy/etc.)
- Understanding of various ETL Tools (e.g., Databricks)
- Knowledge of Linux and Bash scripting basics