Minimum qualifications:- Bachelor's degree in Computer Science, Engineering, Computer Information Systems, Mathematics, Physics, or a related field and 5 years of progressive post-baccalaureate experience in the job offered or in a Data Engineer-related occupation.
- Alternatively, will accept a Master's degree in Computer Science, Engineering, Computer Information Systems, Mathematics, Physics or a related field, and 3 years of experience in the job offered or in a Data Engineer-related occupation.
- Position requires 3 years of experience in the following: Data pipeline design and dimensional data modeling for synchronous and asynchronous system integration; Coding in Python, Java, Go, or C to build and maintain data infrastructure; Data pipeline implementation using external or internal data processing stacks; Data exploration by performing exploratory queries and scripts on data models; and Data consumption and visualization using business intelligence tools including Tableau, Power BI, or DataStudio.
Responsibilities- Design and build secure, scalable, and reliable data processing systems and infrastructure.
- Develop and maintain data models and pipelines to transform data for analysis and machine learning.
- Enable data-driven decisions by analyzing data, profiling systems, and deploying machine learning models.
- Create and consult on data visualizations and reports using various business intelligence tools. Consult with cross-functional partners to define data requirements, standards, and best practices.
- Provide ongoing support to data users by maintaining dashboards, authoring documentation, and delivering training.
The US base salary range for this full-time position is $220,050 - $226,000 15% Bonus Target equity benefits determined by role, level, and location. Individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Learn more about benefits at Google .
Position reports to the Google (Mountain View, CA) office & may allow for a hybrid schedule as per Google policy.
