Databricks Lakehouse Data Engineer (Remote, Flexible)

AgileEngine, LLC.; Buenos Aires; Presencial; ARS 121.018.000 - 211.781.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Growth without limits

Competitive compensation

Remote work 100%

Modern projects with global teams

Collaborative culture

Well-being programs

Descripción de la vacante

AgileEngine is seeking a Middle Data Engineer to modernize a 15-year-old data warehouse into a governed Databricks Lakehouse. You will build batch and streaming pipelines with PySpark and Delta Lake, following a medallion architecture across bronze, silver, and gold layers.

You will use Claude and GitHub Copilot to speed up development and collaborate with DevOps, platform, and analytics engineers on observability, security, and governance.

Formación

• 3+ years of professional data engineering experience with Spark and cloud data architectures.
• Hands-on with Databricks, Spark (PySpark), and Delta Lake.
• Advanced SQL and Python with data modeling across Lakehouse patterns.
• Experience with streaming ingestion using Structured Streaming, Auto Loader, Kafka or Event Hubs.
• Experience with workflow orchestration (Databricks Workflows, Airflow, or Azure Data Factory).
• Experience with legacy platform migrations or ETL modernization.
• Strong problem-solving, collaboration, and communication skills.
• Familiarity with Unity Catalog and data governance.

Responsabilidades

• Design, build, and operate batch and streaming pipelines on Databricks using PySpark, Delta Lake, and Workflows.
• Model and maintain medallion architecture (bronze/silver/gold) for analytics and ML consumers.
• Migrate legacy ETL and data warehouse workloads to the Lakehouse with data parity.
• Use Claude or GitHub Copilot to accelerate development, tests, docs, and prototyping.
• Write clean Python and SQL; ensure quality via reviews and tests.
• Optimize Spark jobs and Delta tables for performance and cost (partitioning, clustering, caching).
• Implement data quality, lineage, and governance with Unity Catalog and automated checks.
• Troubleshoot pipeline failures and production incidents; collaborate on observability and security.

Conocimientos

3+ years data engineering

Problem solving

Communication

Team collaboration

Herramientas

Databricks

Apache Spark (PySpark)

Delta Lake

SQL

Python

Kafka

Airflow

Azure Data Factory

dbt

Unity Catalog

Descripción del empleo

AgileEngine is seeking a Middle Data Engineer to modernize a 15-year-old data warehouse into a governed Databricks Lakehouse. You will build batch and streaming pipelines with PySpark and Delta Lake, following a medallion architecture across bronze, silver, and gold layers.

You will use Claude and GitHub Copilot to speed up development and collaborate with DevOps, platform, and analytics engineers on observability, security, and governance.