Remote Data Quality Engineer for Cloud Analytics

Keyrus Colombia

Colombia

Presencial

COP 192.777.277 - 289.165.916

Jornada completa

14 días+

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Ventajas ofrecidas por este puesto de trabajo

100% remote work

International projects

Work with leading technologies

Training and development

Career growth

Collaborative culture

Descripción de la vacante

Keyrus Colombia is seeking a Quality Engineer for its Enterprise Data Platform practice. You will architect the trust behind the data by building validation frameworks, testing automation, and quality controls across ingestion, transformation, and processing layers in cloud analytics environments.

You will work with data engineers and architects to embed quality into every pipeline, supporting data products from development through deployment and ensuring compliance with data quality dimensions.

Formación

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field, or equivalent professional experience
4+ years of experience in Data Quality Engineering, Data Testing, Quality Assurance, or similar roles supporting enterprise data platforms
Strong SQL skills for validating, reconciling, and analyzing large datasets
Experience with modern cloud-based data platforms and analytics ecosystems
Understanding of ETL/ELT processes, data modeling concepts, dimensional modeling, and data architecture principles
Experience developing and executing automated data validation and testing frameworks
Familiarity with CI/CD practices and integrating quality controls into software and data delivery pipelines
Excellent analytical, troubleshooting, and problem-solving skills
Strong written and verbal communication skills, with the ability to explain technical issues to both technical and business audiences

Responsabilidades

Validate data across ingestion, transformation, integration, and processing workflows to ensure quality, accuracy, and consistency
Perform source-to-target validation and reconciliation across multiple systems and data platforms
Verify business rules, data mappings, transformations, and data lineage throughout the data lifecycle
Ensure compliance with key data quality dimensions, including completeness, accuracy, consistency, timeliness, validity, uniqueness, and referential integrity
Design, develop, execute, and maintain automated and manual testing frameworks for data validation
Implement reusable quality controls and automated testing processes integrated into CI/CD pipelines
Create and maintain test cases, validation rules, test scenarios, and quality documentation
Continuously identify opportunities to automate manual testing and improve testing efficiency
Support enterprise data platforms built on modern cloud technologies and large-scale data ecosystems
Validate data pipelines, orchestration workflows, scheduling processes, and integration components
Monitor pipeline execution and quality controls to proactively identify and resolve issues
Collaborate with engineering teams to ensure the successful deployment of new data products and platform capabilities
Investigate data discrepancies, pipeline failures, and quality issues; perform root cause analysis
Manage defects through their full lifecycle, from identification and documentation through validation and closure
Conduct regression testing to ensure new changes do not negatively impact existing functionality
Participate in User Acceptance Testing (UAT) activities in partnership with business and technical teams
Support release readiness reviews, quality gate assessments, and post-release validation
Contribute to the establishment and continuous improvement of quality standards, testing methodologies, and best practices