About the position
Google Play provides apps, games, and digital content services that bring Android devices to life. The Play Store serves over four billion users around the world, and is a critical driver of Google's overall business growth. With a combination of sharp problem-solving skills and keen commercial acumen, the Play Games Data Science and Analytics (DSA) team provides the insights and operational accuracy that enable Play to delight users, empower developers and create value for Google. As strategic advisors, we collaborate with Product, Engineering, Marketing and other teams in support of Play's loyalty-focused products, including Play Points and Play Pass. In this role, you will work closely with various DSA teams and upstream analytics engineering teams to design and build data marts that will empower and accelerate the DSA team and its stakeholders. You will possess a deep understanding of data scientists and their data requirements and have expertise in architecting data marts, designing and implementing necessary data pipelines, and establishing governance and quality processes to guarantee data availability, usability, and accuracy.
Responsibilities
- Conceptualize and own the build out of problem-solving data marts for consumption by data science and BI teams, evaluating design and operational cost-benefit tradeoffs within systems.
- Design, develop, and maintain robust data pipelines and ETL processes using data platforms for the Play Store organization's centralized data warehouse.
- Create or contribute to frameworks that improve the efficacy of logging data, while working with the Data Infrastructure Engineering team to triage issues and resolve them.
- Scrutinize and validate data integrity throughout the collection process, performing data profiling to identify and comprehend data anomalies.
- Influence product and cross-functional (engineering, data science, marketing, strategy) teams to identify data opportunities to drive impact.
Requirements
- Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
- 10 years of experience coding with SQL or one or more programming languages (e.g., Python, Java, R, etc.) for data manipulation, analysis, and automation.
- 8 years of experience designing data pipelines (ETL) and dimensional data modeling for synchronous and asynchronous system integration and implementation.
- Experience in managing troubleshooting technical issues, and working with Engineering and Sales Services teams.
Nice-to-haves
- Master's degree in Engineering, Computer Science, Business, or a related field.
- Experience with cloud-based services relevant to data engineering, data storage, data processing, data warehousing, real-time streaming, and serverless computing.
- Experience with experimentation infrastructure, and measurement approaches in a technology platform.
- Experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume).
Benefits
- The US base salary range for this full-time position is $180,000-$267,000 + bonus + equity + benefits.
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