Business Intelligence Developer (Python/Streamlit)

TL;DR

Business Intelligence Developer (Python/Streamlit): Designing and developing an internal Python library to standardize Streamlit application development with an accent on creating reusable UI components and AI/LLM wrappers. Focus on transitioning legacy data workloads to modern Streamlit-based tools while maintaining existing data pipelines and ensuring system stability.

Location: Must be physically located in and work from Mexico City (CDMX) or Mexico State (Estado de Mexico)

Company

hirify.global provides customer service software that powers billions of conversations for brands worldwide.

What you will do

• Design and develop an internal Python library to standardize Streamlit application development.
• Create reusable UI components, layout templates, and AI/LLM wrappers for internal data apps.
• Enforce software development best practices including version control, documentation, and automated testing.
• Support and update legacy dashboards in Tableau and Looker.
• Ensure stability of current data systems while migrating workloads to Streamlit.
• Collaborate with the dbt team to define requirements for updating existing data pipelines.

Requirements

• Must be based in Mexico City or Mexico State.
• 3+ years of experience with Python.
• 2+ years of experience with databases and SQL.
• 1+ years of experience in data engineering.
• 1+ years of experience developing with AI coding agents.
• Ability to work in a hybrid environment.

Nice to have

• Experience with Streamlit and dashboard development.
• Knowledge of Snowflake or other cloud data platforms (AWS, GCP, Azure).
• Proficiency with dbt and machine learning concepts.
• Experience with data visualization tools like Tableau or Looker.

Culture & Benefits

• Hybrid work model allowing for in-person collaboration and remote flexibility.
• Inclusive and diverse global work environment.
• Commitment to fairness and transparency in hiring.
• Focus on building impactful data products and modern software engineering practices.