Data Engineer

We're hiring a data engineer to collaborate closely with the Data Science team, implementing robust and scalable data solutions. You will work with Big Data Engineers and Analysts, sharing knowledge and best practices to drive innovation. This role involves developing personalized recommendation systems and prediction models to enhance player enjoyment and engagement, directly impacting game performance. We seek a collaborative data/ML engineer who enjoys learning, with access to mentorship for skill growth.

Must Have

• Build and maintain ML pipelines for deploying and monitoring ML models.
• Implement MLOps best practices in our workflows.
• Integrate data science processes within engineering standards to promote consistency and maintainability.
• Integrate ML Pipelines with products via APIs, databases, or other solutions.
• Provide support to analysts and data scientists, assisting with data exploration, feature engineering, and model deployment.

ABOUT YOU

We’re hiring a data engineer that will collaborate closely with the Data Science team to implement their projects, acting as a key point of contact and translating their needs into robust and scalable data solutions. You will also work closely with Big Data Engineers and Analysts, fostering a collaborative environment to share knowledge, tech stacks, and best practices. This partnership will ensure we leverage collective expertise to build and maintain optimal data solutions, driving innovation and efficiency across the organization.

In this role you will tackle challenging projects like developing personalized recommendation systems to increase player enjoyment and building prediction models to proactively address player needs. Your work will have a measurable impact on our games' performance and be a key driver for player engagement.

We’re looking for a data/ML engineer who enjoys collaborating and learning within a team. You'll have access to mentorship from experienced engineers to help you grow your skills and contribute effectively.

Daily responsibilities

• Build and maintain ML pipelines for deploying and monitoring ML models.
• Implement MLOps best practices in our workflows.
• Integrate data science processes within engineering standards to promote consistency and maintainability.
• Integrate ML Pipelines with products via APIs, databases, or other solutions.
• Provide support to analysts and data scientists, assisting with data exploration, feature engineering, and model deployment.

ABOUT US