Recruiter's Glossary

Examples: Data Modeling • Data Validation • Metrics

Looker

Term from Data Analytics industry explained for recruiters

Looker is a popular tool that helps companies understand their business data through charts, reports, and dashboards. Think of it as a way to turn complex business information into easy-to-understand visual stories. Companies use Looker to track sales, analyze customer behavior, and make better business decisions. It's similar to tools like Tableau or Power BI. Looker connects to different data sources and allows users to explore data without needing advanced technical skills. When someone mentions Looker in their resume, they're typically talking about creating reports, building dashboards, or helping others understand company data.

Examples in Resumes

Created executive dashboards using Looker that improved decision-making efficiency by 40%

Trained team members on Looker and LookML to streamline reporting processes

Developed Looker reports that tracked key business metrics across multiple departments

Typical job title: "Looker Developers"

Also try searching for:

Business Intelligence Developer Data Analyst BI Engineer Analytics Developer Looker Developer Data Visualization Specialist Business Intelligence Analyst

Where to Find Looker Developers

Online Communities

Job Boards

Learning Resources

Professional Networks

Example Interview Questions

Senior Level Questions

Q: How would you approach implementing Looker in a large organization with multiple departments?

Expected Answer: A senior candidate should discuss strategies for organizing data models, managing user permissions, training different teams, and creating standardized reporting processes across departments. They should also mention change management and user adoption approaches.

Q: How do you ensure data quality and performance in Looker dashboards?

Expected Answer: Look for answers about data testing methods, efficient model design, proper indexing of databases, caching strategies, and experience with optimizing complex queries for better performance.

Mid Level Questions

Q: Can you explain how you would create a user-friendly dashboard in Looker?

Expected Answer: Should discuss understanding user needs, selecting appropriate visualizations, organizing information logically, and implementing interactive filters and drill-down capabilities.

Q: What experience do you have with LookML?

Expected Answer: Should be able to explain how they've used LookML to create reusable reporting components, define relationships between different data tables, and create calculated fields.

Junior Level Questions

Q: What types of charts and visualizations have you created in Looker?

Expected Answer: Should be able to describe basic visualization types like bar charts, line graphs, and tables, and explain when to use each type based on the data being shown.

Q: How do you share dashboards and manage permissions in Looker?

Expected Answer: Should understand basic concepts of sharing dashboards with different users, setting up scheduled reports, and basic user access controls.