Remote Data Quality Engineer - GCP & BigQuery Focus

Keyrus Colombia; Colombia; Remote; COP 12,000,000 - 24,000,000; Full time

Benefits offered by this job

100% remote work

International projects

Training and development

Job summary

Keyrus Colombia is seeking a Quality Engineer to ensure trusted data in enterprise Google Cloud Platform environments. You will build validation frameworks, automate tests, and enforce quality controls across ingestion, transformation, and storage layers.

You will work with BigQuery, Dataflow, Cloud Composer, and Cloud Storage, validating ELT/ETL pipelines and monitoring data quality. Collaboration with data engineers and analysts is essential.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• 4+ years of experience in Data Quality Engineering, Data Testing, QA, or similar roles supporting enterprise data platforms.
• Strong SQL skills for validating, reconciling, and analyzing large datasets.
• Hands-on experience with GCP technologies including BigQuery, Dataflow, Cloud Composer, Dataform, and Cloud Storage.

Responsibilities

• Design, develop, and maintain data validation tests across GCP data ecosystems.
• Validate source-to-target data across ingestion, transformation, and storage layers.
• Ensure data quality dimensions: completeness, accuracy, consistency, timeliness, validity, uniqueness, referential integrity.
• Collaborate with Data Engineers and Cloud teams to deploy data products and platform capabilities.

Skills

SQL

GCP (BigQuery, Dataflow)

ETL/ELT testing

Data quality

CI/CD integration

Education

Bachelor's degree in Computer Science or related field

Tools

Cloud Build

GitHub Actions

GitLab CI/CD

BigQuery

Job description

Keyrus Colombia is seeking a Quality Engineer to ensure trusted data in enterprise Google Cloud Platform environments. You will build validation frameworks, automate tests, and enforce quality controls across ingestion, transformation, and storage layers.

You will work with BigQuery, Dataflow, Cloud Composer, and Cloud Storage, validating ELT/ETL pipelines and monitoring data quality. Collaboration with data engineers and analysts is essential.