Remote Data Engineer: Databricks Lakehouse & Pipelines

AgileEngine; Ciudad de Mendoza; Presencial; ARS 135.663.000 - 195.957.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Growth opportunities

Competitive compensation

Remote work with flexible hours

Meaningful, modern projects

Collaborative culture

Well-being & support

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 design and run batch and streaming pipelines with PySpark and Delta Lake for analytics and ML.

Join a hands-on team that leverages Claude and GitHub Copilot to speed development, enforce data governance with Unity Catalog, and optimize Spark performance at scale.

Formación

• 3+ years of professional experience in data engineering with Spark and cloud architectures.
• Hands-on with Databricks, Spark (PySpark), and Delta Lake.
• Advanced SQL and Python with data modeling skills.
• Experience with Structured Streaming, Auto Loader, Kafka or Event Hubs.
• Workflow orchestration: Databricks Workflows, Airflow or Azure Data Factory.
• Experience with legacy migrations, ETL modernization, or maintaining data hygiene.
• Strong problem-solving, collaboration and communication skills.
• Familiarity with Unity Catalog, data governance and PII handling.
• Experience with dbt or equivalent transformation framework.
• Knowledge of secure coding standards and security best practices.
• Experience delivering production data platforms at scale.
• Upper-intermediate English level.

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, reporting, and ML consumers.
• Migrate legacy ETL and data warehouse workloads onto the Lakehouse with minimal disruption.
• Use Claude or Github Copilot to accelerate development, tests, documentation, and prototyping.
• Write clean, well-tested Python and SQL; enforce coding standards and reviews.
• Optimize Spark jobs and Delta tables for performance and cost.
• Implement data quality, lineage, governance using Unity Catalog and automated checks.
• Debug, troubleshoot, and resolve pipeline failures and data defects.
• Collaborate with DevOps, platform, and analytics engineers on observability and security.

Conocimientos

Databricks

PySpark

SQL

Python

Structured Streaming

Airflow

Azure Data Factory

Unity Catalog

dbt

Security best practices

Herramientas

Terraform

Azure DevOps

PostgreSQL

Dynatrace

CloudWatch

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 design and run batch and streaming pipelines with PySpark and Delta Lake for analytics and ML.

Join a hands-on team that leverages Claude and GitHub Copilot to speed development, enforce data governance with Unity Catalog, and optimize Spark performance at scale.