Senior Data Engineer – Data Quality, Observability

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and establish a scalable data quality framework throughout the platform.

• Spearhead the implementation and operationalization of GX Core (Great Expectations) as the main data validation framework.

• Create and sustain reusable data quality rules utilizing a Rule-as-Code methodology.

• Develop automated validation checks for critical business datasets and workflows.

• Implement solutions for data observability, monitoring, alerting, and reporting.

• Define and maintain data lineage across essential business domains.

• Design validation procedures 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 track data quality trends and operational health.

• Investigate the root causes of recurring data issues and implement preventive measures.

• 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 enhance data quality processes and establish long-term observability best practices.

⛳️ Requirements

• Over 5 years of experience as a Data Engineer or in comparable data engineering positions.

• Extensive experience in designing and implementing enterprise Data Quality frameworks.

• Practical experience with GX Core (Great Expectations) or similar tools like Soda.

• Proficient SQL skills and experience working with Aurora PostgreSQL and Amazon Redshift.

• Experience in designing data validation rules, reconciliation processes, and observability solutions.

• Proven experience in building and maintaining ETL pipelines and large-scale data workflows.

• Strong grasp of data modeling, referential integrity, synchronization, and batch processing.

• Experience in integrating data validation into CI/CD pipelines.

• Familiarity with Git and engineering best practices such as Rule-as-Code.

• Experience in creating dashboards, alerts, and reports for operational monitoring.

• Strong analytical and problem-solving capabilities with experience in conducting root cause analysis.

• Experience in collaborating with cross-functional engineering teams.

• Excellent communication and documentation skills.

🏝️ Benefits

• Fully remote position.

• Opportunity to develop 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 engage with modern data validation, observability, and cloud data technologies while driving continuous improvement across the platform.