Self-introduction — Streamlit role

Hi, I’m Danylo — I’m a Python developer with around four years of experience, and over the last several months I’ve been working primarily with Streamlit, which is why this role caught my attention.

Most recent project

A serverless automation platform where I built and maintained two production Streamlit applications.

Census Validator — the one most relevant to your role. A data-entry interface where users:

• Upload Excel files containing reference data
• The app handles automatic tab and header detection, format normalization, and column mapping
• Runs the data through multiple business rule checks
• Returns pass/fail results

So it’s very much a manual interface for managing and validating structured reference data, which sounds close to what you’re describing for the product referential.

Real-time observability dashboard — the second Streamlit app, used by internal teams.

Both were deployed as Docker containers on AWS ECS with Cognito SSO, so I’m also comfortable on the infrastructure side when needed.

Broader stack

Outside of Streamlit, I work across the broader Python ecosystem:

• Lambda functions orchestrated with Step Functions
• DynamoDB
• REST integrations with Salesforce, Microsoft Graph, and Slack

But for this role I’d expect to focus most of that energy on building a clean, reliable Streamlit interface and letting your solution architect drive the architectural decisions.

Happy to go deeper into any of that.

Interview angle

• “When is Streamlit the right tool?” - internal tools, data apps and LLM prototypes where speed of building matters more than UI control. For anything user-facing at scale, a proper frontend against an API is the answer.