Remote Data Engineer – Databricks Lakehouse Specialist

AgileEngine, LLC.; Ciudad de Mendoza; Presencial; ARS 90.763.000 - 136.145.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Growth budget

Competitive pay

Remote work

Modern projects

Collaborative culture

Well-being programs

Descripción de la vacante

AgileEngine is seeking a Middle Data Engineer to modernize a data warehouse into a governed Databricks Lakehouse. You will build batch and streaming pipelines with PySpark and Delta Lake, following a medallion architecture across bronze, silver, and gold layers.

You’ll leverage AI tools like Claude to speed up development. Key responsibilities include migrating legacy ETL workloads, optimizing Spark jobs, and implementing data governance and quality checks.

Formación

• 3+ years in data engineering with Spark and cloud data lakes.
• Hands-on with Databricks, PySpark and Delta Lake for lakehouse models.
• Strong SQL and Python coding for data pipelines and modeling.
• Experience with streaming using Structured Streaming, Kafka or Event Hubs.

Responsabilidades

• Design, build, and operate batch and streaming data pipelines on Databricks.
• Maintain medallion bronze/silver/gold architecture for analytics and ML.
• Migrate legacy ETL workloads to the Lakehouse with validated parity.
• Use Claude or Copilot to accelerate development and testing.
• Write clean Python and SQL, with comprehensive tests and docs.
• Optimize Spark jobs and Delta tables for performance and cost.
• Implement data quality, lineage, and governance controls.
• Debug and resolve production data issues and incidents.
• Collaborate with DevOps and analytics teams on observability and security.

Conocimientos

3+ years of data engineering

Databricks PySpark Delta Lake

SQL

Python

Structured Streaming Kafka

Databricks Workflows Airflow ADF

Unity Catalog data governance

dbt

Herramientas

Terraform

Azure DevOps

PostgreSQL

Descripción del empleo

AgileEngine is seeking a Middle Data Engineer to modernize a data warehouse into a governed Databricks Lakehouse. You will build batch and streaming pipelines with PySpark and Delta Lake, following a medallion architecture across bronze, silver, and gold layers.

You’ll leverage AI tools like Claude to speed up development. Key responsibilities include migrating legacy ETL workloads, optimizing Spark jobs, and implementing data governance and quality checks.