Senior Data Engineer, Play Data Science and Analytics

Minimum qualifications:

• 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 (Extract, Transform, Load) 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.

Preferred qualifications:

• 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).

About the job

In this role, you will work with various Data Science and Analytics (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 an understanding of data scientists and their data requirements and have experience in architecting data marts, designing and implementing necessary data pipelines, and establishing governance and quality processes to guarantee data availability, usability, and accuracy.

The US base salary range for this full-time position is $180,000-$267,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Responsibilities

• Conceptualize and own the build out of problem-solving data marts for consumption by data science and business intelligence teams, evaluating design and operational cost-benefit tradeoffs within systems.
• Design, develop, and maintain data pipelines and ETL (Extract, Transform, Load) 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.
• 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.