Data Engineer: Databricks, PySpark & GCP Specialist

Agileengine; San Carlos de Bariloche; Híbrido; ARS 136.828.000 - 228.047.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive compensation

Exciting projects

Flextime

Descripción de la vacante

AgileEngine is seeking a Data Engineer with strong Databricks and GCP experience to design and productionize scalable ETL/ELT pipelines and agentic workflows for data automation.

You will design, implement, and optimize data pipelines across Databricks, PySpark, SQL, and BigQuery, while ensuring data quality and robust production controls. The role emphasizes collaboration with cross-functional teams and ongoing automation opportunities.

Formación

• 5+ years of strong 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.

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

Advanced SQL

BigQuery

Delta Lake

ETL/ELT design

Production-grade

Troubleshooting

Software engineering practices

Descripción del empleo

AgileEngine is seeking a Data Engineer with strong Databricks and GCP experience to design and productionize scalable ETL/ELT pipelines and agentic workflows for data automation.

You will design, implement, and optimize data pipelines across Databricks, PySpark, SQL, and BigQuery, while ensuring data quality and robust production controls. The role emphasizes collaboration with cross-functional teams and ongoing automation opportunities.