Remote Data Quality Engineer — Build Trusted Data

BairesDev; Chile; Presencial; CLP 82.267.000 - 109.689.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote work

USD salary option

Hardware provided

Flexible hours

Paid parental leave

Vacations & holidays

Mentorship & growth

Global team

Descripción de la vacante

BairesDev is seeking a Data Quality Engineer to ensure the reliability and integrity of data across our pipelines. You will lead automated testing and validation to detect anomalies and maintain high data standards.

You will design checks, deploy quality tooling, build anomaly detection, and collaborate with data engineers to define metrics while enabling visibility through reporting across the global data ecosystem.

Formación

• 4+ years of experience in Data Quality Engineering, Data Engineering, or Data Analytics.
• Proven expertise in building automated data quality checks and validation rules.
• Hands-on experience with data testing tools such as Great Expectations, Deequ, or Soda.
• Demonstrated ability to implement anomaly detection across distributed data pipelines.
• Advanced proficiency in English.

Responsabilidades

• Design and implement automated data quality checks and validation rules across various data pipelines.
• Deploy and manage data quality tooling such as Great Expectations, Deequ, or Soda to monitor data health.
• Develop anomaly detection models to identify and mitigate data drift or integrity issues.
• Collaborate with data engineers and stakeholders to define data quality metrics and standards.
• Build reporting systems to provide visibility into data quality and reliability across the data ecosystem.

Conocimientos

Data quality

Automated checks

Great Expectations

Deequ

Soda

Anomaly detection

English proficiency

Herramientas

Great Expectations

Deequ

Soda

Descripción del empleo

BairesDev is seeking a Data Quality Engineer to ensure the reliability and integrity of data across our pipelines. You will lead automated testing and validation to detect anomalies and maintain high data standards.

You will design checks, deploy quality tooling, build anomaly detection, and collaborate with data engineers to define metrics while enabling visibility through reporting across the global data ecosystem.