Data Engineer, Data Architecture and Engineering, gTech Strategy and Operations

• Design, develop, test, and maintain reliable and scalable data pipelines and Extract, Transform, Load and Extract, Load, Transform (ETL/ELT) architectures using Google's distributed data systems (e.g., advanced SQL, Python).
  
• Contribute to the modernization of the Google Ads Data Infrastructure (GDI) and Customer Data Platform (CDP), optimizing data models to ensure our Single Source of Truth remains robust and performant.
  
• Partner closely with cross-functional stakeholders across gTech and Customer Engagement (CE) to translate evolving business requirements into actionable technical data solutions.
  
• Work seamlessly with Data Scientists and Business Analysts to transition analytical prototypes, metrics, and models into stable, production-grade reporting environments.
  
• Advocate data quality by authoring clear technical design documents, executing code reviews, and proactively resolving complex bugs and support escalations.
  

Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
• 1 year of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume).
  
• Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams.
• Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript.
  

Preferred qualifications:

• Master's degree or other advanced degree in Computer Science or related technical field or equivalent practical experience.
• Experience in technical consulting and working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments.
• Experience working with Big Data, information retrieval, data mining, or machine learning.
  
• Experience in building multi-tier high availability applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow).
  
• Experience in a customer-facing or customer service role, with practice using AI technologies to augment, improve, or automate the development process.

• Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
• 1 year of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume).
  
• Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams.
• Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript.