Senior Data Engineer – Redshift | Data Quality & Observability1789

SOFTGIC; Villa Adelina; Presencial; ARS 134.860.000 - 224.766.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Fully remote

High impact role

Collaborative team

Modern data tech

Descripción de la vacante

SOFTGIC is seeking a Senior Data Engineer to lead the data quality and observability program. You will implement a modern data quality framework, operationalize GX Core, establish validation standards, and build observability solutions to improve confidence across reporting and workflows.

You will drive data quality practices, define lineage, and integrate validations into CI/CD with cross-functional collaboration. Strong SQL, Big data, and cloud data tooling are essential.

Formación

• 5+ years of experience as a Data Engineer or in similar data engineering roles.
• Experience designing enterprise Data Quality frameworks.
• Hands-on with GX Core (Great Expectations) or Soda.
• Strong SQL skills with Aurora PostgreSQL and Redshift.

Responsabilidades

• Design and implement a scalable data quality framework across the platform.
• Lead the implementation and operationalization of GX Core 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.

Conocimientos

Data engineering

Data quality

Observability

SQL

Great Expectations

Soda

Git

CI/CD

Herramientas

GX Core (Great Expectations)

Soda

Aurora PostgreSQL

Amazon Redshift

Git

Descripción del empleo

Senior Data Engineer Redshift | Data Quality & Observability1789

BARRIO ARCA, Argentina | Posted on 08/06/2026

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.

Requirements

• 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.