Senior Databricks Lakehouse Engineer

Agileengine; Mar del Plata; Híbrido; ARS 181.094.000 - 271.641.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive USD-based compensation

Exciting projects with Fortune 500 and

Flextime and remote-friendly

Descripción de la vacante

AgileEngine in Argentina is seeking a Senior Data Engineer to design and operate batch and streaming pipelines on Databricks, using PySpark and Delta Lake. You will migrate legacy data workloads to a governed Lakehouse, modeling a medallion architecture to power analytics and AI use cases.

You'll write clean Python and SQL, optimize Spark jobs, implement data quality and governance with Unity Catalog, and collaborate across DevOps, platform, and analytics teams.

Formación

• 3+ years of professional experience in data engineering.
• Direct expertise with Apache Spark and cloud-based data architectures.
• Strong SQL and Python with data modeling skills.
• Experience with Structured Streaming, Auto Loader, Kafka, or Event Hubs.
• Experience with Databricks Workflows, Airflow, or Azure Data Factory.
• Experience with Unity Catalog, data governance, and PII handling.
• Experience with dbt or an equivalent transformation framework.
• Familiarity with secure coding practices.

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 serving analytics, reporting, and machine learning consumers.
• Migrate legacy ETL and data warehouse workloads onto the Lakehouse with validated data parity and minimal business disruption.
• Use Claude or GitHub Copilot as a development accelerator, generating code scaffolding, writing and reviewing tests, creating documentation, and prototyping solutions.
• 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, including partitioning, clustering, caching, and cluster sizing.
• Implement data quality, lineage, and governance controls using Unity Catalog and automated validation checks.
• Debug, troubleshoot, and resolve pipeline failures, data defects, and production incidents.
• Collaborate with DevOps, platform, and analytics engineers on observability, security, and compliance best practices.

Conocimientos

Apache Spark

Databricks

PySpark

Delta Lake

SQL

Python

Data modeling

Medallion architecture

Problem solving

Herramientas

Databricks

Delta Lake

Airflow

Azure Data Factory

Databricks Workflows

Unity Catalog

dbt

Kafka

Descripción del empleo

AgileEngine in Argentina is seeking a Senior Data Engineer to design and operate batch and streaming pipelines on Databricks, using PySpark and Delta Lake. You will migrate legacy data workloads to a governed Lakehouse, modeling a medallion architecture to power analytics and AI use cases.

You'll write clean Python and SQL, optimize Spark jobs, implement data quality and governance with Unity Catalog, and collaborate across DevOps, platform, and analytics teams.