Databricks Data Engineer — Spark, Delta Lake, Lakehouse

AgileEngine, LLC.; Ciudad de Mendoza; Presencial; ARS 135.820.000 - 196.185.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive USD-based compensation

Exciting projects

Flextime

Descripción de la vacante

AgileEngine is seeking a Data Engineer to build batch and streaming data pipelines on Databricks using PySpark and Delta Lake. This role migrates legacy data workloads to a governed Lakehouse for analytics and AI use cases with robust data modeling.

You will collaboratively design, implement, and optimize data pipelines, governance, and performance while maintaining tests and documentation in an agile environment.

Formación

• 4+ years of professional experience in data engineering.
• Experience with Apache Spark, PySpark, Delta Lake, and cloud data architectures.

Responsabilidades

• Design, build, and operate batch and streaming data pipelines on Databricks using PySpark, Delta Lake, and Databricks Workflows.
• Model and maintain a medallion (bronze/silver/gold) architecture for analytics, reporting, and ML.
• Migrate legacy ETL and data warehouse workloads onto the Lakehouse with parity and minimal disruption.
• Use Claude or GitHub Copilot to generate code scaffolding, tests, docs, and prototypes.
• Write clean Python and SQL; ensure quality through reviews and docs.
• Optimize Spark jobs and Delta tables for performance and cost.
• Implement data quality, lineage, governance using Unity Catalog and validation checks.
• Debug and resolve pipeline failures and production incidents.
• Participate in Agile/product delivery (sprint planning, retros).
• Collaborate with DevOps, platform, and analytics engineers on observability, security, compliance.

Conocimientos

Apache Spark

Databricks

SQL

Python

Data modeling

Cloud architecture

Agile

Herramientas

Databricks Workflows

Airflow

Azure Data Factory

Terraform

PostgreSQL

Descripción del empleo

AgileEngine is seeking a Data Engineer to build batch and streaming data pipelines on Databricks using PySpark and Delta Lake. This role migrates legacy data workloads to a governed Lakehouse for analytics and AI use cases with robust data modeling.

You will collaboratively design, implement, and optimize data pipelines, governance, and performance while maintaining tests and documentation in an agile environment.