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.