Data QA Engineer (AI)

Location: Prishtina, Kosovo. Office-based or hybrid options are available.

Company

hirify.global develops a shipment-tracking platform that turns device sensor data into customer-facing analytics and AI agents, helping customers reduce shipment delays, rejected loads, theft, damage, and spoilage.

What you will do

• Own the data quality strategy for Snowflake, dbt, and Airflow pipelines, selecting checks according to pipeline layer and customer impact.
• Write and maintain dbt tests for uniqueness, nullability, accepted values, referential integrity, timestamp order, value ranges, and business logic using built-in, generic, unit, dbt_utils, and dbt_expectations tests.
• Monitor pipeline health by configuring freshness and anomaly tests, tuning alert severity and thresholds, and maintaining data-health dashboards.
• Review pull requests for test coverage and data risk, improve CI testing, and involve QA before data models are released.
• Build evaluation datasets and test suites for AI agents, including golden question sets, verified answers and SQL, scoring rubrics, and metrics for accuracy, SQL correctness, tool selection, grounding, and latency.
• Analyze agent traces and production failures, route fixes to the appropriate prompt, semantic layer, data model, or source-data owner, and report quality trends to product and leadership teams.

Requirements

• 4+ years of experience in data QA, analytics engineering, or data engineering with a quality focus.
• Strong SQL skills, including reading complex dbt models, determining grain and join risks, and writing validation queries to quantify issues.
• Hands-on dbt experience with tests, contracts, schema.yml documentation, sources, freshness, and incremental model failure modes.
• Experience with a cloud data warehouse, preferably Snowflake.
• Experience designing data tests with judgment and keeping alerts rare and actionable.
• Working understanding of LLMs and agents, including non-determinism, hallucinations, tool use, and evaluation of variable outputs.
• Comfort with Git, pull request reviews, and CI.
• Clear technical writing, including turning data problems into actionable engineering tickets and explaining quality results to non-technical stakeholders.

Nice to have

• Experience with Elementary, dbt_utils, dbt_expectations, or Snowflake data metric functions.
• Experience with LLM evaluation tools such as LangSmith, Braintrust, MLflow, DeepEval, or Snowflake Cortex Analyst evaluations.
• Experience evaluating text-to-SQL or analytics agents, or building semantic layers.
• Airflow experience and experience building BI dashboards with Sigma or similar tools.
• Use of AI coding assistants for model review, test generation, and failure triage.
• Experience with IoT, sensor, or logistics data.

Culture & Benefits

• Autonomy and resources to build and improve data quality systems.
• Work with a global team built around transparency, simplicity, mutual support, and continuous improvement.
• Office-based or hybrid work options.
• Competihirify.global equity providing ownership in hirify.global's long-term growth.
• Equal-opportunity employment and an inclusive environment based on mutual respect.