Data Infrastructure Engineer
Job Overview
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Job Description
About the Job
As a Data Infrastructure Engineer within Google Customer Solutions (GCS), you will be crucial in building and maintaining the core data infrastructure that powers our Sales and Partner teams. This infrastructure enables these teams to effectively execute on product objectives and drive sustainable business growth for Small and Medium Businesses (SMBs) globally. You will collaborate extensively with cross-functional teams, overseeing aspects of data infrastructure, solution design, and development, including requirements gathering, testing, documentation, training, implementation, and ongoing support. Your work will directly support the Product and Sales Activation (PSA) team, enhancing performance and brand solutions for SMB advertisers.
Responsibilities
- Operate a stable data infrastructure, collaborating closely with Engineering teams and partners to continuously improve processes across various cross-functional stakeholders.
- Develop and maintain robust data models, pipelines, and SQL scripts essential for the visualization, analysis, and interpretation of complex data sets.
- Perform in-depth data analysis and profiling using relevant tools, leveraging existing data infrastructure and models with minimal guidance to enable data-driven decision-making.
- Work proactively with internal clients to identify their data needs, clarify requirements, and collect, transform, and publish data effectively.
- Adhere to and enhance technical best practices, ensuring data discoverability, considering the full data lifecycle, and proficiently managing master data.
Minimum Qualifications
- Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
- 3 years of experience analyzing data, creating reports, and utilizing database query tools (e.g., SQL) and visualization tools (e.g., Tableau, dashboards).
- Experience with one or more general-purpose programming languages (e.g., Python, C/C++, Java).
Preferred Qualifications
- Master’s degree in a quantitative or a related field.
- Proficiency in data visualization and dashboard tools such as Tableau, PowerBI, or Looker.
- Familiarity with Google Ads products.
- Proven ability to manage multiple projects with varying priorities effectively.
- Excellent communication and presentation skills to convey analytical findings clearly.
- Strong organizational and project management capabilities.
Compensation
The US base salary range for this full-time position is $124,000-$178,000, complemented by bonus opportunities, equity, and comprehensive benefits. Individual pay is determined by factors such as work location, job-related skills, experience, and relevant education or training.
Key Skills/Competency
- Data Infrastructure
- SQL
- Data Modeling
- Data Pipelines
- Python
- Data Analysis
- Tableau
- Cross-functional Collaboration
- Process Improvement
- Database Management
How to Get Hired at Google
- Research Google's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume for impact: Customize your resume to highlight data infrastructure, SQL, Python, and collaboration skills for Google roles.
- Prepare for technical interviews: Practice SQL querying, data modeling, and coding challenges in Python, C++, or Java relevant to Google's engineering standards.
- Showcase problem-solving and collaboration: Be ready to discuss how you've designed and maintained complex data systems and worked with diverse teams at Google.
- Demonstrate genuine curiosity: Express your interest in Google Customer Solutions and how your skills align with their mission to empower SMBs.
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