Data Quality Analyst

About the Role

As a Data Quality Analyst, you will be responsible for identifying, diagnosing, and coordinating the resolution of data inconsistencies across our different models and products. Working closely with the data team, you will monitor data pipelines, validate estimates, investigate anomalies, and ensure our outputs tell a consistent story over time.

This is an independent role - you will need to take initiative, define best practices, and proactively catch and escalate data quality issues before they impact our clients.

Newzoo operates in a hybrid work environment (part office, part work from home), and English is the primary language used for communication.

Key Responsibilities

• Ensure consistent and logical output of estimates across different models and reporting periods.
• Coordinate with the data team and key stakeholders to make sure issues are prioritized, resolved, and communicated upon.
• Triage issues, scanning data sources to quickly find the step where an issue is introduced.
• Develop and maintain DBT data quality tests and framework (not_null, unique, accepted_values, and custom SQL tests).
• Monitor and debug DBT pipeline failures and data freshness issues in BigQuery.
• Identify unexpected spikes, drops, or inconsistencies in estimates using SQL-based anomaly detection.
• Work closely with data owners, data engineers, and modelers to ensure that proposed solutions fully resolve the issue.
• Document data issues, assumptions, and test results to track quality over time.
• Work proactively—when you see an issue, you take the lead in coordinating its resolution.
• Communicate findings clearly to technical and non-technical stakeholders.

What We’re Looking For

✅ 3+ years of relevant work experience in data quality, analytics, or a related field.

✅ Proactive, independent problem solver – You take ownership of data issues and drive them to resolution with the right stakeholders.

✅ Strong SQL skills (BigQuery experience preferred) – You can query large datasets efficiently and diagnose anomalies.

✅ BI tool expertise (Metabase, Tableau, etc.) – You can easily analyze and navigate large datasets to identify trends, inconsistencies, and potential data quality issues.

✅ DBT expertise – Experience writing DBT tests and debugging data pipeline issues.

✅ Understanding of ETL & Data Pipelines – You know how data moves through a system and where things can break.

✅ Experience working in an Agile environment, particularly with SCRUM, managing tight deadlines and adapting to shifting priorities.

✅ Data anomaly detection – Experience setting up validation checks and investigating inconsistencies.

✅ Basic statistics knowledge – Ability to recognize trends and unusual patterns in data.

✅ Experience in a fast-moving, data-driven environment – You understand the importance of consistency over time.

✅ Excellent documentation skills – You can clearly explain your findings, assumptions, and recommendations.

Nice to Have (But Not Required)

• A passion for video game trends and market dynamics.
• Experience with Elementary, Monte Carlo, Datafold, or other data observability tools.
• Familiarity with Python for automating validation processes.