Senior Databricks Data Engineer | Remote Growth & Impact

AgileEngine; Córdoba; A distancia; ARS 135.892.000 - 196.289.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Growth opportunities

Competitive compensation

Remote work

Modern projects

Collaborative culture

Well-being programs

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 design and run batch and streaming pipelines with PySpark and Delta Lake, applying a medallion architecture for analytics, reporting, and ML use cases.

You will migrate legacy workloads, leverage Claude and Copilot to accelerate development, and write clean Python and SQL while ensuring governance and test coverage.

Formación

• 4+ 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, 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.
• 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 (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

Apache Spark

Databricks

SQL

Python

Data modeling

Cloud data architectures

Mentoring

English fluency

Herramientas

Delta Lake

Databricks Workflows

Airflow

Azure Data Factory

dbt

Unity Catalog

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 design and run batch and streaming pipelines with PySpark and Delta Lake, applying a medallion architecture for analytics, reporting, and ML use cases.

You will migrate legacy workloads, leverage Claude and Copilot to accelerate development, and write clean Python and SQL while ensuring governance and test coverage.