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Full Stack Engineer - Analytics
Glu Mobile
San Francisco
7 months ago
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We’re looking for an innovative Full-Stack Engineer who will help us in building out a world-class revenue platform. The work will include building front-to-back web applications that live on top of our analytics platform, utilizing a variety of technologies including Angular, Node, Redis, Druid, DynamoDB, and Kubernetes. These applications will support: optimizing the workflow of our user acquisition team; enabling game developers to provide fine-grained control over their users’ experiences; detailed reporting on KPIs and custom metrics with advanced querying features; and real-time data stream visualizations of current game activities.
The ideal candidate has an engineering background with attention to code quality, who is looking to apply those skills to build robust, high-visibility web applications. We are passionate about maximizing the value that our data can provide to our business. This is a fantastic opportunity to use your engineering skills to make a material impact on a highly valued revenue platform!
Responsibilities:
- Develop high quality web applications in Angular 8 / Node.js which leverage our data platform and technologies like Redis, Spark, Druid, and DynamoDB
- Work with server and analytics engineering teams to architect and design back-end interfaces for applications
- Evangelize best practices for front-end architecture and design
- Work with Product Management and other business partners to design new features and novel applications that push boundaries
Qualifications:
- Bachelor’s degree in computer science / Mathematics / Engineering, or other field with proven engineering experience
- 3-5 years software engineering experience, especially working on front-end data applications
- Proficiency with front-end languages and frameworks, especially recent versions of Angular
- Proficiency with at least one server-side framework (e.g. Node or Spring) and related concepts, such as async programming, caching, and databases
- Experience with SQL and SQL-like languages is a plus
- Bonus for experience with big data technologies such as Druid, Cassandra, DynamoDB, and Spark
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