Data Quality Engineer

Responsibilities:

• Develop and maintain advanced automated data quality checks for game telemetry, player events, and backend systems.
• Monitor complex data pipelines for anomalies, schema changes, and integrity issues, ensuring high availability and reliability.
• Define, document, and enforce global data quality standards, validation rules, and SLAs across the data ecosystem.
• Lead collaboration with engineering teams to ensure accurate and scalable instrumentation of in-game events.
• Investigate and resolve complex data discrepancies, performing deep root-cause analysis to prevent recurrence.
• Build and oversee dashboards and alerting systems to surface data quality issues in real time for stakeholders.
• Partner with analytics and product teams to ensure data sets are optimized and fit for strategic decision-making.
• Map and document data definitions, lineage, and quality expectations to improve organizational data literacy.
• Support technical compliance efforts related to player data privacy.

Who We Think Will Be A Great Fit:

• Problem Solving and Analytical Thinking: Ability to diagnose complex technical issues within large-scale data environments and implement systemic solutions.
• Attention to Detail: A rigorous approach to data accuracy and the ability to identify subtle patterns or anomalies in high-volume datasets.
• Cross-Functional Collaboration: Proven ability to work effectively with both technical engineering teams and non-technical product stakeholders.
• Communication: Skill in translating complex data quality issues into actionable insights and clear technical documentation.
• Proactivity: A self-driven mindset focused on identifying potential risks and improving observability before issues impact the business.

Requirements:

• Bachelor's degree in Computer Science, Data Engineering, or a related technical field (or equivalent experience).
• Extensive experience in data engineering, data quality, or analytics engineering, typically requiring 5+ years of relevant experience.
• Advanced SQL proficiency and expertise in managing and querying large, complex.
• Hands-on experience with data pipeline and orchestration tools (e. g., Airflow, dbt, Spark).
• Deep understanding of data validation frameworks and automated testing
• Proven experience working with high-volume, event-based data such as telemetry, logs, and user activity streams.

Preferred Qualifications:

• Experience within the gaming industry or similar high-concurrency, real-time data.
• Mastery of specialized data quality tools (e. g., Great Expectations, Monte Carlo).
• Proficiency with cloud platforms and data warehouses (e. g., AWS, Databricks, Snowflake).
• Familiarity with A/B testing frameworks and the nuances of experimentation.
• Knowledge of global data privacy regulations (e. g., GDPR, CCPA) and best practices for player data governance.