Data Engineer — Databricks/GCP, Flexible & Remote

AgileEngine, LLC.; Santiago de Querétaro; Híbrido; MXN 700.000 - 1.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive compensation

Exciting projects

Flextime

Descripción de la vacante

AgileEngine, LLC. is seeking a Data Engineer with strong Databricks and GCP experience to develop scalable ETL/ELT pipelines and automate agentic workflows for data engineering automation.

You will design, build, and optimize data pipelines using Databricks, PySpark, and SQL, integrate with BigQuery and Delta Lake, and create reusable components to support fast-growing data needs across multiple projects.

Formación

• 5+ years of hands-on Databricks and PySpark experience.
• Advanced SQL and data-processing skills.
• GCP experience, particularly BigQuery.
• Delta Lake and modern data lake architectures.
• Experience building reliable, production-grade data solutions.

Responsabilidades

• Design and optimize scalable ETL/ELT data pipelines.
• Build and operationalize agentic workflows for automation.
• Integrate with Databricks, GCP, BigQuery, and Delta Lake environments.
• Develop data pipelines and processing solutions for new datasets and business needs.
• Create reusable data engineering frameworks and components.
• Implement data quality checks, monitoring, and production controls.
• Optimize PySpark and SQL workloads for performance.
• Support testing, deployment, and productionization of data solutions.
• Troubleshoot complex data and production issues.
• Collaborate with cross-functional teams to identify further automation opportunities.

Conocimientos

Databricks

PySpark

Advanced SQL

BigQuery

Delta Lake

Herramientas

Databricks UI

BigQuery Console

Git

Descripción del empleo

AgileEngine, LLC. is seeking a Data Engineer with strong Databricks and GCP experience to develop scalable ETL/ELT pipelines and automate agentic workflows for data engineering automation.

You will design, build, and optimize data pipelines using Databricks, PySpark, and SQL, integrate with BigQuery and Delta Lake, and create reusable components to support fast-growing data needs across multiple projects.