Senior Data Quality Engineer — Remote & Flexible Hours

BairesDev; Montes de María; Remote; COP 191,883,000 - 319,806,000; Full time

Benefits offered by this job

Remote work

USD/local currency pay

Home office setup

Flexible hours

Parental leave

Growth opportunities

Multicultural team

Mentorship

Job summary

BairesDev is a 15-year technology partner delivering cutting-edge solutions to global leaders and startups with a 4,000+ remote team. The Senior Data Quality Engineer role focuses on automating data quality frameworks within lakehouse environments to ensure complete, reliable data assets and strict SLAs.

You’ll collaborate across engineering teams to address data defects while enabling scalable data reliability.

Qualifications

• 5+ years of experience in Data Engineering or Data Quality.
• Expertise in data quality automation within lakehouse environments.
• Hands-on experience implementing automated DQ validation and regression testing.
• Knowledge of schema drift detection and Great Expectations or Deequ frameworks.
• Advanced proficiency in English.

Responsibilities

• Design and implement automated data quality validation frameworks across pipelines and data products.
• Develop robust mechanisms for schema drift detection to capture format variations dynamically.
• Establish and enforce data completeness SLAs to guarantee high-integrity data availability.
• Build automated regression testing suites tailored to lakehouse architectures.
• Partner with engineering teams to identify, isolate, and resolve structural data defects.

Skills

Data quality

Data engineering

Databricks lakehouse

DQ validation

Schema drift detection

Great Expectations/Deequ

English

Tools

Databricks

Great Expectations

Deequ

Job description

BairesDev is a 15-year technology partner delivering cutting-edge solutions to global leaders and startups with a 4,000+ remote team. The Senior Data Quality Engineer role focuses on automating data quality frameworks within lakehouse environments to ensure complete, reliable data assets and strict SLAs.

You’ll collaborate across engineering teams to address data defects while enabling scalable data reliability.