Senior Data Engineer: Databricks & GCP Pipelines

Agileengine; Partido de Quilmes; Presencial; ARS 152.309.000 - 228.464.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive USD-based compensation

A selection of exciting projects

Flextime

Descripción de la vacante

AgileEngine is seeking a Data Engineer to design, develop, and optimize scalable ETL/ELT pipelines using Databricks, PySpark, and SQL. You will build agentic workflows to automate data engineering tasks and validation, integrating with Databricks, GCP, BigQuery, and Delta Lake environments.

You will develop data pipelines for new datasets, create reusable frameworks, implement data quality checks, and collaborate with cross-functional teams to drive automation and data-driven decisions.

Formación

• 5+ years hands-on with Databricks and PySpark.
• Advanced SQL and data-processing skills.
• GCP experience, especially BigQuery.
• Delta Lake and modern data lake/lakehouse architectures.
• ETL/ELT design, data pipeline design, performance optimization, and data quality.
• Production-grade, scalable data solutions experience.

Responsabilidades

• Design, develop, and optimize scalable ETL/ELT pipelines with Databricks, PySpark, SQL.
• Build agentic workflows to automate data engineering tasks and validation.
• Integrate with existing Databricks, GCP, BigQuery, and Delta Lake environments.
• Develop data pipelines and processing solutions for new datasets.
• Build reusable frameworks across data engineering use cases.
• Implement data quality checks, monitoring, and production controls.
• Collaborate with business and platform teams to identify further automation opportunities.

Conocimientos

Databricks

PySpark

SQL

GCP

BigQuery

Delta Lake

ETL/ELT

Data pipelines

Descripción del empleo

AgileEngine is seeking a Data Engineer to design, develop, and optimize scalable ETL/ELT pipelines using Databricks, PySpark, and SQL. You will build agentic workflows to automate data engineering tasks and validation, integrating with Databricks, GCP, BigQuery, and Delta Lake environments.

You will develop data pipelines for new datasets, create reusable frameworks, implement data quality checks, and collaborate with cross-functional teams to drive automation and data-driven decisions.