VARTEQ Inc. is a remote-first IT outsourcing and product company with teams across the US, Europe, and LatAm. We build scalable data and AI-driven solutions for clients in fintech, edtech, and enterprise software. This role sits at the intersection of data engineering and quality assurance, focusing on validating ETL/ELT pipelines, data transformations, and the reliability of ML model outputs. You’ll collaborate with data engineers, ML engineers, and product stakeholders to define quality standards and contribute to automated testing frameworks. Our environment is async-friendly, client-facing, and performance-driven, with opportunities to influence data quality practices across multiple client engagements.

What you’ll bring: 2+ years in QA, with at least 1 year focused on data or AI pipeline testing. Proficiency in Python for test automation (pytest, custom scripts). Solid SQL skills to validate data across sources. Hands-on experience with data quality frameworks (Great Expectations, dbt tests, Soda, or similar). Strong understanding of ETL/ELT concepts and pipeline architecture. Familiarity with workflow orchestration tools (Airflow or similar). Upper-intermediate English (B2+).

Nice to have: Experience testing ML model outputs (predictions, scoring, drift detection). Familiarity with data warehouses (Snowflake, BigQuery, Redshift). Knowledge of data observability tools (Monte Carlo, Metaplane). Experience with CI/CD integration for data tests (GitHub Actions, GitLab CI).