Google, an American tech giant with internet-related products and services ranging from operating systems (Android, Chrome OS) to mobile and desktop applications (Google Chrome, Google Adwords, etc.) and from hardware (Google Nexus line) to services like Google Cloud, Youtube TV, etc.
Founded in 1998, the company is headquartered in Mountain View, California. Google’s corporate mission is to “organize the world’s information and make it universally accessible and useful” and this is only possible through data.
Data is important to Google, which is why they own and operate over 20 data centers around the world. With over 3.55 billion search queries processed daily and 5 billion Youtube videos watched per day, Google is one of the most “data-rich companies in the world” and the best spot for data analysts, data scientists, and business analysts to build their careers.
Business analysts at Google analyze data to develop different insights to drive business decisions for products, answering questions such as “How do we make the product better?” and “What do users like about the product?”.
Google has a strong data culture and business analysts use this data to inform and drive business decisions. Roles may differ slightly based on which team an analyst is assigned to, but the general role at Google ranges from identifying solutions and new business insights through extensive data analysis and predictive modelling to requirements management and communication of insights to relevant stakeholders.
The role of a business analyst at Google requires field specialization and extensive industry experience. As such, Google only employs the most qualified applicants with a minimum of 4 years (7+ for senior roles) of industry experience in quantitative analysis, consulting, or any relevant data-driven business roles.
Other basic qualifications include:
The Google business analyst interview is just like every other Google interview process. It starts with an online phone interview with a recruiter, and then you proceed to the technical screen interview with a manager. After the technical, the recruiter will then schedule an onsite interview, which comprises three to four one-on-one interview rounds with a lunch break in between.
This is the first interview step with a recruiter or HR, and it is mainly exploratory. In this 45-minute interview, the recruiter will ask questions about your relevant past experiences and projects, especially those that involve SQL. The recruiter will also provide insights into the company, job roles, and the company’s work culture.
Note: In this interview, you should answer every question with a story or an experience that demonstrates your fit for the role using real-life examples and data.
Sample Questions:
Google’s business analyst technical screen follows almost the same protocol as most Google technical interviews. Standard case-based SQL questions are asked, and candidates are required to write SQL queries on a shared Google Doc.
Questions are standardized, so solving SQL questions from Interview Query can better prepare you for this interview.
The business analyst onsite interview comprises three interview rounds with a manager, a product specialist, and a business analyst, all lasting between 30 and 45 minutes.
Google interview candidates are assessed on four general attributes: “general cognitive ability, leadership, role-related knowledge, and Googleyness”. Every interview question is wrapped around those four basic attributes, and candidates are expected to shape their answers accordingly.
The schedule for a Google business analyst onsite interview looks like this:
This is an interview with a manager, and questions are standard case-based SQL questions.
Google’s business analyst interview assesses candidates’ ability to leverage data analytics to identify key business insights, provide solutions, and help make sound, strategic business decisions. Interview questions cover mainly conceptual level data science knowledge, predictive modelling, metrics and strategy definition, and the ability to communicate insights to stakeholders. Brush up on your knowledge of descriptive analytics, statistics and probability, time-series, regression, and predictive modelling.
Brush up on your SQL skills and learn basic to advanced tips and tricks.
Average Base Salary
Average Total Compensation