Senior Data Engineer – Data Quality & Observability |1789
buenos aires, Argentina
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingDesign 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.
From the employer’s posting
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.
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.
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.
Tools in this posting
- SQL
- PostgreSQL
- Redshift
Source — Tool mentions in context
- 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.
Job description
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.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on softwareestrategico.zohorecruit.com. The employer’s form will show what is required.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
buenos aires, Argentina
What We Offer - ? Fully remote position. - ? Opportunity to build enterprise-scale data quality and observability solutions.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Jul 25, 2026
- Recorded sightings
- 146
- Last seen by us
- Oct 8, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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