Remote Data Engineer, Databricks Lakehouse

AgileEngine; Perímetro Urbano Barranquilla; Presencial; COP 281.461.000 - 406.555.000; 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 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.

This role also uses AI tools like Claude and Github Copilot to speed up development. You will design, implement, and optimize data pipelines, governance, and testing, collaborating with DevOps, platform, and analytics

Formación

• 3+ years of professional experience in data engineering with Spark and cloud data architectures.
• Hands-on experience building data pipelines with Databricks, Apache Spark (PySpark), and Delta Lake.
• Advanced SQL and Python with data modeling skills across dimensional and Lakehouse patterns.
• Experience with Structured Streaming, Auto Loader, Kafka, or Event Hubs.
• Experience with Databricks Workflows, Airflow, or Azure Data Factory.
• Experience with legacy 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.
• 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.
• Collaborate with DevOps, platform, and analytics engineers on observability, security, and compliance best practices.

Conocimientos

Databricks

Apache Spark (PySpark)

Delta Lake

SQL

Python

Structured Streaming

Kafka

Databricks Workflows

Airflow

Unity Catalog

dbt

Security best practices

Production data platforms

English (Upper-intermediate)

Herramientas

Databricks Workflows

SQL

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.

This role also uses AI tools like Claude and Github Copilot to speed up development. You will design, implement, and optimize data pipelines, governance, and testing, collaborating with DevOps, platform, and analytics