[Hiring] Data Quality Engineer @CNX

Role Description

We are seeking a highly skilled Data Engineering - Quality Engineer to define and implement end-to-end testing strategies for a modern data platform built on AWS. This role will be responsible for ensuring data quality, reliability, and performance across the entire pipeline; from ingestion to transformation and reporting; within the Redshift BI Foundations program.

• Define the end-to-end testing scope based on solution architecture and project OPM documentation
• Design and implement a comprehensive testing strategy and plan aligned with organizational QA standards
• Develop and maintain test scripts and frameworks for the Redshift BI Foundations platform
• Perform testing across key technologies, including:
  • AWS Redshift
  • AWS DMS (Data Migration Service)
  • AWS Glue
  • Terraform
  • Python-based data pipelines
  • Apache Airflow (via Astronomer managed interface)
  • dbt (data build tool)
  • Soda.io (data quality and observability)
• Build and implement automated testing solutions to ensure:
  • End-to-end data validation
  • Data ingestion accuracy
  • Transformation logic integrity
  • Data pipeline reliability
• Conduct test coverage analysis and ensure adequate validation across all data engineering workflows
• Prepare and manage test data
• Review and provide feedback on:
  • Solution architecture
  • Data models
  • Design and technical documentation
• Collaborate with cross-functional teams (Data Engineering, BI, DevOps, Product) to:
  • Identify testing impacts
  • Mitigate risks
  • Ensure high-quality deliverables

Qualifications

• Proven experience in data engineering testing / data QA / ETL validation
• Strong hands-on experience with AWS data services (Redshift, Glue, DMS)
• Proficiency in Python for test automation and validation
• Experience with Airflow (Astronomer preferred) and orchestration testing
• Hands-on experience with dbt and data transformation validation
• Familiarity with Terraform for infrastructure validation
• Experience in BI testing in Tableau will be highly beneficial
• Experience with data quality tools such as Soda.io or similar
• Strong understanding of:
  • Data warehousing concepts
  • ETL/ELT pipelines
  • Data validation techniques (schema, reconciliation, anomaly detection)

Requirements

• Experience designing enterprise-level test strategies for data platforms
• Knowledge of CI/CD pipelines for data and test automation
• Experience working in Agile / Scrum environments
• Familiarity with data observability frameworks

Benefits

• Medical, dental, and vision insurance
• Comprehensive employee assistance program
• 401(k) retirement plan
• Paid time off and holidays