Data Engineer - Remote Databricks Lakehouse & AI Pipelines

AgileEngine, LLC.; Mar del Plata; Presencial; ARS 90.763.000 - 151.272.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Growth budget

Competitive pay

Remote work

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 design batch and streaming pipelines with PySpark and Delta Lake across bronze, silver, and gold layers.

You will leverage AI tools like Claude and GitHub Copilot to accelerate development, implement data governance with Unity Catalog, and collaborate with DevOps, platform, and analytics engineers to ensure performance, security, and reliability.

Formación

• 3+ years of professional experience in data engineering with Spark and cloud data architectures.
• Strong hands-on experience building data pipelines with Databricks, Apache Spark (PySpark), and Delta Lake.
• Advanced SQL and Python with strong data modeling skills across dimensional and 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, ETL modernization, or managing data hygiene when porting old systems.
• Strong problem-solving, collaboration, and communication skills.
• Familiarity with Unity Catalog, data governance, access control, and PII handling.
• Experience with dbt or an equivalent transformation framework.
• Familiarity with secure coding standards and industry security best 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 ML 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

PySpark

Delta Lake

SQL

Python

Data modeling

Streaming

Databricks Workflows

Airflow

Data governance

Herramientas

Databricks

Auto Loader

Kafka

Event Hubs

Azure Data Factory

Terraform

Azure DevOps

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 batch and streaming pipelines with PySpark and Delta Lake across bronze, silver, and gold layers.

You will leverage AI tools like Claude and GitHub Copilot to accelerate development, implement data governance with Unity Catalog, and collaborate with DevOps, platform, and analytics engineers to ensure performance, security, and reliability.