[Hiring] Lead Data Quality Engineer @EPAM

Role Description

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.

• 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.

Qualifications

• 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.

Requirements

• 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.