BI Engineer for AI-Powered Data Apps

Zendesk; Estado de México; Híbrido; MXN 480.000 - 720.000; Jornada completa

Descripción de la vacante

Zendesk is seeking a versatile BI Developer focused on blending software engineering, dashboard development, and AI/Cloud technologies. The role requires a strong Python foundation, agile collaboration, and curiosity to build impactful data products that emphasize the “why” behind the code.

You will design a reusable Python library for Streamlit apps, maintain legacy dashboards, and work with DBT and data platforms in a hybrid Mexico City environment.

Formación

• Python: strong foundation and 3+ years experience.
• Databases: experience with SQL and data pipelines.
• SQL: in-depth querying and data modeling.
• Data Engineering: basic experience building data pipelines.
• AI Usage: experience developing with AI tooling and agents.

Responsabilidades

• Design and develop an internal Python library to streamline Streamlit app development.
• Create reusable UI components and AI wrappers to empower teams building data apps.
• Enforce software development best practices, including version control, packaging, documentation, and tests.
• Support and update legacy dashboards in Tableau/Looker and transition workloads to Streamlit-based tools.
• Collaborate with DBT and data platform teams (e.g., Snowflake) to update pipelines.

Conocimientos

Python

Databases

SQL

Data Engineering

AI Usage

Streamlit

AI agents skills development

Dashboard development

Snowflake

DBT

Machine Learning

Data Visualization Tools

Herramientas

Python libraries

Descripción del empleo

Zendesk is seeking a versatile BI Developer focused on blending software engineering, dashboard development, and AI/Cloud technologies. The role requires a strong Python foundation, agile collaboration, and curiosity to build impactful data products that emphasize the “why” behind the code.

You will design a reusable Python library for Streamlit apps, maintain legacy dashboards, and work with DBT and data platforms in a hybrid Mexico City environment.