Senior/Lead Data Quality Engineer
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.
Responsibilities
- 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
Requirements
- 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
Nice to have
- 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)
