Analytics Engineer — ELT/Dashboards & AI Enablement (Hybrid)

Darwin AI; Ciudad de México; Híbrido; MXN 300.000 - 520.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Language Classes

OpenAI Premium License

Paid Time Off 25 days

Soft Hybrid Work

Descripción de la vacante

Darwin AI in Mexico City is seeking a Semi-Senior Analytics Engineer to own the ELT pipeline and design dashboards that keep the company data-driven. You will work with product, sales and operations to extract actionable insights and support data-informed decision making across the business.

We value 2–4 years of analytics or data engineering experience, strong SQL, production Python, and familiarity with Airflow or Dagster and dbt to transform data and accelerate AI initiatives.

Formación

• 2–4 years of experience in data analytics or data engineering.
• Strong SQL querying skills.
• Experience with Python in production and version control.
• Experience with Airflow or Dagster orchestrators.
• Experience with dbt data transformation.
• Excellent problem-solving and clear business communication.
• English reading/writing proficiency; speaking is a plus.

Responsabilidades

• Own the entire ELT pipeline to provide the company with the data they need
• Design, develop and maintain dashboards for our company to be data-driven
• Work closely with cross-functional teams to help them be more data-driven
• Support the optimization of AI performance with data analytics
• Document and present findings to stakeholders in a clear and concise manner

Conocimientos

SQL proficiency

Python production

Data analytics

Stakeholder communication

English proficiency

Herramientas

Airflow

Dagster

dbt

Descripción del empleo

Darwin AI in Mexico City is seeking a Semi-Senior Analytics Engineer to own the ELT pipeline and design dashboards that keep the company data-driven. You will work with product, sales and operations to extract actionable insights and support data-informed decision making across the business.

We value 2–4 years of analytics or data engineering experience, strong SQL, production Python, and familiarity with Airflow or Dagster and dbt to transform data and accelerate AI initiatives.