Agility Partners is seeking a skilled Data Quality Engineer to join the team of a leading grocer in the Cincinnati area and play a critical role in ensuring the reliability, accuracy, and consistency of data within their warehouse and manufacturing data platform in the supply chain space.
Key Responsibilities:
- Collaborate with data engineers to understand data pipelines, transformations, and business rules to develop comprehensive test strategies.
- Design, implement, and maintain test frameworks for validating data quality, completeness, and accuracy across all stages of the data lifecycle.
- Develop automation test scripts using Python and PySpark to execute test cases against data pipelines and processes.
- Conduct regression testing to ensure the stability and reliability of data pipelines after code changes or updates.
- Implement monitoring and alerting mechanisms to proactively identify and address data quality issues in production environments.
- Work closely with cross-functional teams to define acceptance criteria and ensure that data quality requirements are met.
- Document test cases, test results, and defects to facilitate collaboration and knowledge sharing within the team.
- Continuously evaluate and improve testing processes and methodologies to enhance data quality assurance practices.
- Stay updated on emerging technologies and trends in data quality engineering, and incorporate them into our testing practices as appropriate.
Benefits and Perks
Reasons to Love It:
If you have experience in an agile environment and a passion for using servant leadership to deliver amazing solutions, apply to be a part of our innovative culture built on the foundation of generations of success.
- Hybrid work schedule
- Working for an organization that focuses on company culture, inclusion, and diversity
- 50% medical coverage for you and your entire family, short/long term disability, and life insurance options
- 401(k)
- Life Insurance
The Ideal Candidate
Qualifications:
- Proficiency in data engineering technologies such as Azure Databricks, Synapse Analytics, and SQL Hyperscale.
- Strong programming skills in Python and PySpark for developing automation test scripts.
- Experience with building and implementing test frameworks for data-centric applications in Azure cloud environments.
- Knowledge of data quality assurance methodologies and best practices.
- Familiarity with version control systems and CI/CD pipelines for automated testing and deployment.
- Understanding of data modeling, ETL processes, and data warehousing concepts.
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