Senior Data & Analytics Engineer — Snowflake & dbt

Secreto; Buenos Aires; Híbrido; ARS 182.310.000 - 227.887.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive USD-based compensation

Exciting projects

Flextime

Descripción de la vacante

AgileEngine is seeking a Senior Data and Analytics Engineer to build data pipelines and analytical models that support business intelligence and strategic decision‑making in the media and entertainment industry.

You will work with Snowflake, dbt Cloud, GitHub, VS Code, and Python to deliver robust data features, translate complex use cases into data models, and collaborate with product managers and analysts to ensure consumption-ready data.

Formación

• 4+ years in data engineering or analytics engineering within production.
• Expert-level Python and SQL skills.
• Strong proficiency with Snowflake and development tools like GitHub and VS Code.
• Thrives in a process-light environment similar to a data science team.
• Excellent communication with non-technical stakeholders and product managers.

Responsabilidades

• Deliver robust data features and pipelines within project teams for fast-paced business verticals.
• Translate complex use cases into robust data models using dbt and SQL.
• Build and maintain scalable pipelines using Snowflake, dbt Cloud, GitHub, VS Code, and Python.
• Collaborate with leadership to adopt AI tools and governance within projects.
• Partner with product managers and analysts to deliver consumption-ready data.

Conocimientos

Python

SQL

Snowflake

GitHub

VS Code

Data engineering

Analytics engineering

dbt Cloud

Herramientas

dbt Cloud

Snowflake

GitHub

VS Code

Descripción del empleo

AgileEngine is seeking a Senior Data and Analytics Engineer to build data pipelines and analytical models that support business intelligence and strategic decision‑making in the media and entertainment industry.

You will work with Snowflake, dbt Cloud, GitHub, VS Code, and Python to deliver robust data features, translate complex use cases into data models, and collaborate with product managers and analysts to ensure consumption-ready data.