Senior Data Engineer – Data Quality & Observability |1789

Are you passionate about building reliable, scalable data platforms and improving data quality at an enterprise level? We are looking for a Senior Data Engineer – Data Quality & Observability to lead the implementation of a modern data quality framework, enabling engineering teams to detect, monitor, and prevent data issues before they impact business operations.

In this role, you'll drive the implementation of engineering-owned data quality practices, operationalize GX Core, establish validation standards, and build observability solutions that improve confidence across reporting, synchronization processes, and operational workflows.

• Design and implement a scalable data quality framework across the platform.
  
• Lead the implementation and operationalization of GX Core (Great Expectations) as the primary data validation framework.
  
• Develop and maintain reusable data quality rules using a Rule-as-Code approach.
  
• Create automated validation checks for business-critical datasets and workflows.
  
• Implement data observability, monitoring, alerting, and reporting solutions.
  
• Define and maintain data lineage across key business domains.
  
• Design validation processes for data completeness, accuracy, integrity, consistency, reconciliation, freshness, and anomaly detection.
  
• Integrate data quality validations into CI/CD pipelines and release processes.
  
• Develop dashboards and reports to monitor data quality trends and operational health.
  
• Investigate root causes of recurring data issues and implement preventive solutions.
  
• Collaborate with Data Engineering, Application Engineering, QA, Product, and Support teams to establish ownership and governance for data quality.
  
• Define standards for governance, validation frequency, remediation workflows, and quality metrics.
  
• Continuously improve data quality processes and establish long-term observability best practices.
  

• 5+ years of experience as a Data Engineer or in similar data engineering roles.
  
• Strong experience designing and implementing enterprise Data Quality frameworks.
  
• Hands-on experience with GX Core (Great Expectations) or similar tools such as Soda.
  
• Strong SQL skills and experience working with Aurora PostgreSQL and Amazon Redshift.
  
• Experience designing data validation rules, reconciliation processes, and observability solutions.
  
• Experience building and maintaining ETL pipelines and large-scale data workflows.
  
• Strong understanding of data modeling, referential integrity, synchronization, and batch processing.
  
• Experience integrating data validation into CI/CD pipelines.
  
• Experience with Git and engineering best practices such as Rule-as-Code.
  
• Experience building dashboards, alerts, and reporting for operational monitoring.
  
• Strong analytical and problem-solving skills with experience performing root cause analysis.
  
• Experience collaborating with cross-functional engineering teams.
  
• Excellent communication and documentation skills.
  

• ? Fully remote position.
  
• ? Opportunity to build enterprise-scale data quality and observability solutions.
  
• ? High-impact role with ownership over data quality strategy and engineering best practices.
  
• ? Collaborative environment working alongside Data Engineering, QA, Product, and Application Engineering teams.
  
• ? Opportunity to work with modern data validation, observability, and cloud data technologies while driving continuous improvement across the platform.