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Senior/Lead Data Quality Engineer

Віддалений* формат співпраці з території - Україна

*Ви можете працювати віддалено з території країни (або країн), для яких відкрита ця позиція.

Data Quality Engineering
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Our team is looking to hire a talented Senior/Lead Data Quality Engineer. In this role, you will be instrumental in safeguarding the integrity, reliability, and quality of our data engineering platforms and pipelines.

Чим ви будете займатися у цій ролі
  • Build and architect a strong automated testing strategy and framework for data engineering pipelines, emphasizing integration with Databricks, PySpark, Scala, Spark SQL, and other pertinent technologies
  • Deploy automated tests that guarantee data quality, integrity, and reliability across every data pipeline and platform
  • Embed automated testing into Azure DevOps CI/CD pipelines to enable smooth testing, build, and deployment workflows
  • Carry out performance testing to evaluate the scalability and efficiency of data processing systems
  • Collaborate closely with data engineers and additional stakeholders to gather requirements and align testing strategies with business goals
  • Set up monitoring for automated tests and deliver routine reports covering test coverage, defects, and data quality concerns
Навички
  • At least 3 years of experience working in Data Quality Engineering or an adjacent field
  • Strong grasp of data engineering principles and automated testing frameworks
  • Hands-on expertise with Databricks, PySpark, Scala, Spark SQL, Terraform, and Azure Event Hubs
  • Background in connecting testing frameworks to Azure DevOps and handling source control through Git
  • Understanding of pipeline configuration and deployment using Terraform
  • Working knowledge of Jira
  • Excellent analytical skills with a demonstrated history of diagnosing and resolving complex testing and data issues
  • English proficiency at a B2+ level
Буде перевагою
  • Exposure to Power BI, Azure Data Lake, Spark Streaming, and additional data visualization and processing tools
  • Previous work in a data-heavy industry or within large-scale data environments
  • Skill in delivering solutions via Infrastructure as Code (IaC)