Senior Databricks Engineer - Remote & Lakehouse Pipelines

AgileEngine, LLC.; Mar del Plata; Híbrido; ARS 135.820.000 - 196.185.000; 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 Senior Data Engineer to design and build batch and streaming data pipelines on Databricks using PySpark and Delta Lake. This role will migrate legacy ETL workloads to a governed Lakehouse, empowering analytics and AI use cases with a medallion architecture.

You will apply strong SQL and Python skills, optimize Spark jobs, and implement data quality and governance using Unity Catalog, collaborating with DevOps and analytics peers to ensure reliability and security.

Formación

• 3+ years of professional experience in data engineering.
• Experience with Apache Spark and cloud-based data architectures.
• Databricks, Apache Spark (PySpark), and Delta Lake expertise.
• Advanced SQL and Python skills with data modeling across dimensional and Lakehouse patterns.

Responsabilidades

• Design, build, and operate batch and streaming data pipelines on Databricks using PySpark, Delta Lake, and Databricks Workflows.
• Model and maintain a medallion architecture (bronze/silver/gold) for analytics, reporting, and ML consumers.
• Migrate legacy ETL and data warehouse workloads onto the Lakehouse with validated data parity and minimal disruption.
• Write clean, well-tested Python and SQL; maintain high standards through code review and documentation.
• Optimize Spark jobs and Delta tables for performance and cost.

Conocimientos

Apache Spark

Databricks

PySpark

Delta Lake

SQL

Python

Structured Streaming

Kafka

Airflow

Unity Catalog

dbt

Herramientas

Databricks Workflows

Azure Data Factory

Descripción del empleo

AgileEngine is seeking a Senior Data Engineer to design and build batch and streaming data pipelines on Databricks using PySpark and Delta Lake. This role will migrate legacy ETL workloads to a governed Lakehouse, empowering analytics and AI use cases with a medallion architecture.

You will apply strong SQL and Python skills, optimize Spark jobs, and implement data quality and governance using Unity Catalog, collaborating with DevOps and analytics peers to ensure reliability and security.