Defend Fit and Data Infrastructure

You are interviewing for a Pricing Analyst role at a food company. You do not have direct pricing experience, but your background includes SQL/Python/R work and résumé projects involving ETL and reporting automation.

The interviewer asks a combined set of questions:

• Is it correct that you do not have direct pricing experience?
• Do you have any financial-analysis experience, even if it was academic or project-based?
• Most of our work is done in Google Sheets rather than SQL/Python/R. How comfortable are you with that?
• What is the most complex model, workflow, or analysis you have built and maintained in Google Sheets or a similar spreadsheet tool?
• On your résumé, you say you built an ETL pipeline to preprocess 25,000 CSV files . How exactly did files arrive? Where were they extracted from? What made the pipeline truly automated rather than manual or semi-automated? What triggered the transform step? What centralized database was used, and was the pipeline ever productionized?
• More broadly, how should a candidate demonstrate "exact experience" when their background is adjacent rather than identical to the job description?

Prepare a strong interview answer that positions you as a credible hire despite the domain gap. Your answer should:

1. Explain the transferable skills that make you relevant for pricing work.
2. Show how you would ramp up on pricing-specific metrics such as revenue, gross margin, unit volume, markdown rate, and spoilage/waste .
3. Address the trade-off between spreadsheet-based workflows and code-based workflows.
4. Walk through the ETL system clearly from source -> landing/storage -> transformation -> database -> reporting/consumption .
5. Make your decision points and tool trade-offs explicit.