About the role
This is a remote position.
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.
Responsibilities * 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.
Requisitos
* 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.
What We Offer * ? 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.
Originally posted on Himalayas