Senior Databricks Data Engineer | Flexible Growth

Agileengine; Buenos Aires; Presencial; ARS 135.820.000 - 181.094.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive USD-based compensation

Exciting projects

Flextime and hybrid work

Descripción de la vacante

AgileEngine is seeking a Senior Data Engineer to build batch and streaming pipelines on Databricks using PySpark and Delta Lake. You will migrate legacy workloads to a governed Lakehouse and enable analytics and AI use cases with strong SQL, Python, and Unity Catalog governance.

You will collaborate with DevOps, platform, and analytics teams, optimize Spark jobs, and implement data quality and security best practices to support Fortune 500 clients and innovative projects.

Formación

• 3+ years of professional experience in data engineering with direct expertise in Spark and cloud data architectures.
• Strong SQL and Python with data modeling across Lakehouse patterns.
• Experience with streaming ingestion and orchestration tools (Spark Structured Streaming, Auto Loader, Kafka, Event Hubs).
• Experience with data governance and Unity Catalog; dbt or equivalent transformation frameworks.

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 serving analytics and ML consumers.
• Migrate legacy ETL and data warehouse workloads onto the Lakehouse with minimal business disruption.
• Write clean, well-tested Python and SQL; participate in code reviews and documentation.

Conocimientos

3+ years data engineering

Apache Spark

Databricks

Delta Lake

SQL

Python

Structured Streaming

Kafka

Databricks Workflows

Airflow

Azure Data Factory

Unity Catalog

dbt

secure coding

Herramientas

Databricks Workflows

Airflow

Azure Data Factory

Terraform

Descripción del empleo

AgileEngine is seeking a Senior Data Engineer to build batch and streaming pipelines on Databricks using PySpark and Delta Lake. You will migrate legacy workloads to a governed Lakehouse and enable analytics and AI use cases with strong SQL, Python, and Unity Catalog governance.

You will collaborate with DevOps, platform, and analytics teams, optimize Spark jobs, and implement data quality and security best practices to support Fortune 500 clients and innovative projects.