Data Engineer: Databricks & GCP, Remote/Flextime

AgileEngine; Ciudad de Mendoza; Híbrido; ARS 152.309.000 - 213.233.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth opportunities

Competitive USD-based compensation

Projects with Fortune 500 clients

Flextime with remote work options

Descripción de la vacante

AgileEngine is seeking a Data Engineer to design and optimize scalable data pipelines using Databricks, PySpark, and SQL. You will build agentic workflows, integrate with BigQuery and Delta Lake, and ensure production-grade reliability across data platforms.

The role emphasizes data quality, performance tuning, and collaboration with cross-functional teams to automate data workflows and accelerate insights.

Formación

• 5+ years hands-on experience with Databricks and PySpark.
• Advanced SQL and data-processing skills.
• Hands-on experience with GCP, particularly BigQuery.
• Experience with Delta Lake and modern data lake/lakehouse architectures.
• Strong understanding of ETL/ELT, data pipeline design, performance optimization, and data quality.
• Experience building reliable, scalable, production-grade data solutions.
• Strong analytical and troubleshooting skills.
• Understanding of software engineering practices, including testing, version control, deployment, monitoring, and production support.
• Upper-intermediate English level.

Responsabilidades

• Design, develop, and optimize scalable ETL/ELT data pipelines using Databricks, PySpark, and SQL.
• Build and operationalize agentic workflows to automate data engineering and operational processes such as data validation, issue identification, troubleshooting, and workflow execution.
• Integrate agentic capabilities with existing Databricks, GCP, BigQuery, and Delta Lake environments.
• Develop data pipelines and processing solutions to support new business requirements and datasets.
• Build reusable frameworks and components that can be leveraged across multiple data engineering and business use cases.
• Implement data quality checks, monitoring, validation, exception handling, and production controls.
• Optimize PySpark and SQL workloads for performance, reliability, and scalability.
• Support testing, deployment, productionization, and ongoing enhancement of data and agentic solutions.
• Troubleshoot complex data and production issues and implement sustainable solutions.
• Collaborate with business, data engineering, and platform teams to identify further automation opportunities.

Conocimientos

Databricks

PySpark

SQL

GCP

ETL/ELT design

Production-grade data solutions

Performance optimization

Data quality checks

Troubleshooting

Software engineering practices

Herramientas

BigQuery

Delta Lake

Descripción del empleo

AgileEngine is seeking a Data Engineer to design and optimize scalable data pipelines using Databricks, PySpark, and SQL. You will build agentic workflows, integrate with BigQuery and Delta Lake, and ensure production-grade reliability across data platforms.

The role emphasizes data quality, performance tuning, and collaboration with cross-functional teams to automate data workflows and accelerate insights.