Senior Databricks Engineer — Lakehouse & AI Analytics

Agileengine; San Miguel de Tucumán; Híbrido; ARS 135.820.000 - 196.185.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive USD-based compensation

Flextime with remote and office option

Descripción de la vacante

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

Strong SQL, Python, and governance experience are required. You will collaborate with DevOps and analytics engineers to ensure observability, security, and compliance, while optimizing Spark jobs and data quality checks

Formación

• 3+ years of professional data engineering experience required.
• Strong SQL and Python skills with data modeling expertise.
• Experience with Spark, Databricks, Delta Lake & Lakehouse architectures.
• Experience with streaming ingestion and data governance.
• Familiarity with Unity Catalog and PII handling.

Responsabilidades

• Design, build, and operate batch and streaming pipelines on Databricks.
• Model medallion architecture for analytics and ML.
• Migrate legacy ETL to Lakehouse with minimal disruption.
• Write tests and documentation; review code.
• Optimize Spark jobs and Delta tables for performance and cost.
• Implement data quality and governance controls.
• Collaborate with DevOps and analytics engineers on observability and security.
• Debug production incidents and data defects.

Conocimientos

SQL

Python

Problem solving

Communication

Collaboration

Herramientas

Databricks

Apache Spark

Delta Lake

Unity Catalog

Databricks Workflows

Airflow

Azure Data Factory

Kafka

Event Hubs

dbt

Terraform

PostgreSQL

CloudWatch

Descripción del empleo

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

Strong SQL, Python, and governance experience are required. You will collaborate with DevOps and analytics engineers to ensure observability, security, and compliance, while optimizing Spark jobs and data quality checks