Data Engineer III, Global Business and Operations Engineering
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Minimum qualifications:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 3 years of experience coding with one or more programming languages (e.g., Python, Java, C/C++).
- 3 years of experience designing data pipelines (ETL) and model data, for synch and asynch system integration and implementation.
- 3 years of experience analyzing data, database query (e.g., SQL), and creating dashboards/reports.
Preferred qualifications:
- Master’s degree in Engineering or Computer Science.
- 3 years of experience partnering with stakeholders (e.g., users, partners, customers).
- 3 years of experience developing project plans and delivering projects on time within budget and scope.
- Experience with BigQuery or similar cloud-based data warehousing technologies.
- Experience with data pipeline tools (e.g., Dataflow, Apache Airflow, Apache Beam).
- Excellent communication and collaboration skills.
About the job
Global Business and Operations Engineering (GBO) is an embedded Product and Engineering team within Google’s ad sales organization. The team builds consumer-grade internal tooling for sales, marketing, and service teams.
The cross-functional team of engineers, designers, and product managers is responsible for internal platforms that support Sales and Marketing teams to run events, deliver professional services, and manage commercial agreements with ads customers.
As a Data Engineer, you will play a key part in building the foundational data infrastructure that powers Google's advertising products. You will be responsible for designing, developing, and maintaining a scalable data warehouse solution that serves the needs of internal teams and drives value for customers.
Responsibilities
- Design, build, and maintain ETL pipelines to transform data from various sources.
- Develop and manage the data warehouse storage layer, leveraging Google BigQuery and other technologies.
- Create and maintain data marts and presentation layers to support reporting and analysis needs.
- Collaborate with product owners, business stakeholders, and data analysts to understand data requirements and translate them into technical solutions.
- Ensure data quality, accuracy, and consistency across the data warehouse.
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