Senior Databricks Data Engineer — Remote, High-Impact Pipelines

AgileEngine, LLC.; Rosario; Presencial; ARS 1.800.000 - 3.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Growth without limits

Competitive compensation

Flexibility: 100% remote with flexible

Meaningful, modern projects

Collaborative culture

Well-being & support

Descripción de la vacante

AgileEngine is seeking an experienced Senior 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.

This role leverages AI tools like Claude and GitHub Copilot to speed up development, and you will mentor teammates while driving data quality, governance, and scalable solutions across analytics and ML use cases.

Formación

• 4+ years of professional experience in data engineering.
• Expertise with Databricks, Apache Spark (PySpark), and Delta Lake.
• Advanced SQL and Python with strong modeling skills.
• 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, including mentoring junior engineers and explaining data concepts to non-technical stakeholders.
• 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 machine learning 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.
• Participate in Agile or product-centric delivery practices including sprint planning and retrospectives.
• Collaborate with DevOps, platform, and analytics engineers on observability, security, and compliance best practices.

Conocimientos

SQL

Python

Apache Spark (PySpark)

Data modeling

ETL pipelines

Mentoring

Herramientas

Databricks

Delta Lake

Databricks Workflows

Airflow

Azure Data Factory

dbt

Descripción del empleo

AgileEngine is seeking an experienced Senior 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.

This role leverages AI tools like Claude and GitHub Copilot to speed up development, and you will mentor teammates while driving data quality, governance, and scalable solutions across analytics and ML use cases.