Explain pricing fit and ETL architecture

You are interviewing for a Pricing Analyst / Data Analyst role at a food company. The interviewer is less interested in buzzwords and more interested in whether your past work is real, reproducible, and operationally sound.

Give a structured answer to the following:

1. You do not have direct pricing experience. How would you honestly acknowledge that gap while showing transferable experience from analytics, financial analysis, forecasting, operations, or experimentation?
2. Most of the team works in Google Sheets rather than a heavier SQL/Python/BI workflow. How would you explain your comfort level with Sheets, and what is the most complex model, process, or reporting workflow you have built or maintained in that environment?
3. What technical infrastructure are you most comfortable with, and why?
4. On your résumé you claim that you built an ETL pipeline to preprocess roughly 25,000 CSV files . Describe the system end to end:
   • Where did the data come from?
   • How was it received (email, SFTP, API, shared drive, cloud bucket, manual upload, etc.)?
   • Where was it extracted to?
   • What transformations were applied?
   • What triggered the pipeline (manual run, cron/scheduler, file-arrival event, orchestration tool)?
   • What made it manual, semi-automated, or fully automated?
   • What centralized database or warehouse did it load into?
   • Was it ever productionized, monitored, and used by downstream stakeholders?
5. Throughout your answer, make the trade-offs explicit: why the chosen tools were appropriate, what limitations they had, and how data flowed from source to storage to business consumption.

The interviewer is explicitly testing whether you can articulate decision points, tool trade-offs, and data infrastructure, not just list technologies.