Data Quality Engineer

Overview

Join our team as a Data Quality Engineer in a dynamic and remote role where you ll enhance data reliability across diverse platforms. This position offers an excellent opportunity to be at the forefront of data observability and AI pipeline efficiency.

• Develop and optimize data quality monitoring tools using advanced platforms.
• Ensure data integrity by configuring monitoring for freshness, volume, and schema changes.
• Embed data quality controls into ingestion and transformation processes to uphold standards.
• Address data quality alerts through thorough investigation and root cause analysis.
• Collaborate with cross-functional teams to resolve and prevent recurring data quality issues.
• Enhance AI pipeline performance by supporting data observability efforts.
• Document solutions and continuously refine monitoring and alert mechanisms.

• Over four years of experience in data engineering or quality-related roles.
• Strong command of SQL and experience with large-scale datasets.
• Proficiency in utilizing data observability tools, particularly Monte Carlo.
• Solid analytical skills for conducting root cause assessments on data disruptions.
• Excellent communication skills to collaborate effectively with diverse teams.

• Expertise in data quality for AI and advanced analytics environments.
• Understanding of data lineage, catalogs, and governance systems.
• Experience in compliance-heavy sectors like finance or healthcare.
• Familiarity with CI/CD and automated validation patterns for data pipelines.

We are committed to fostering an inclusive environment at Horizontal where diversity, equity, and inclusion are integral to our culture. We welcome applicants from all backgrounds to apply and contribute to creating equitable opportunities for everyone.

Once you apply for this position, you may receive a phone call, SMS or email at the time of application from our Virtual AI Recruiter, Alex, to conduct an initial interview.