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Zynga

Posted 29 Oct 2026

Data Quality Engineer

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Employment
Full time
Team
Data Science & Analytics
Posted
29 Oct 2026

About the role

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.

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