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Tripledot Studios, one of the world's largest independent mobile games companies with 2,500+ employees across 12 studios and 25+ million daily active users, is seeking a Senior Data Engineer to join its central AI team.
You will lead the design and implementation of a game event data hub that consolidates data from multiple studios. Your initial focus will be on data ingestion, preparation, and quality assurance—ensuring the team has visibility into data asset health and can respond quickly to pipeline failures. You'll work closely with studio data engineers to ensure solutions align with their existing patterns and needs.
Key responsibilities include:
- Building and operating the game event data hub, ingesting data from multiple studios
- Developing and orchestrating data ingestion, preparation, quality checks, and backfills
- Centralizing dataset metadata and data quality information using tools like OpenMetadata to provide visibility into data asset health
- Improving monitoring and alerting systems so teams are notified when pipelines or data assets require attention
- Coordinating with studio data engineers to keep shared solutions aligned with their technical patterns and requirements
- Contributing to productionizing and maintaining machine learning pipelines as you rotate across team responsibilities
This is a new senior role with significant scope for technical leadership and cross-functional collaboration. Over time, you'll expand into other areas of the AI team's work, including ML pipeline productionization and maintenance.
Requirements:
- Proven experience building and operating data pipelines, including ingestion, preparation, data quality checks, backfills, and orchestration
- Working knowledge of Kubernetes, Airflow, SQL, and Spark
- Practical, reliable approach to delivering work and maintaining systems
- Strong ability to collaborate constructively with engineers within your team and across studios
Nice to have:
- Experience in the games industry (domain knowledge can be learned)
- Experience with change data capture or streaming technologies
- Exposure to machine learning workflows
- Knowledge of Kubeflow
