Databricks Lakehouse Data Engineer — Remote

AgileEngine, LLC.; Centrosur; Presencial; COP 6.000.000 - 9.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote work

Flexible hours

Learning budget

Mentorship

Competitive pay

Descripción de la vacante

AgileEngine is seeking a Middle Data Engineer to modernize a data warehouse into a Databricks Lakehouse. Build batch and streaming pipelines with PySpark and Delta Lake, following a medallion architecture across bronze, silver, and gold layers. AI tools like Claude and GitHub Copilot accelerate development.

You will migrate legacy workloads, implement governance with Unity Catalog, and collaborate with DevOps and analytics teams to ensure performance and data quality at scale.

Formación

• Must have 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 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 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 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)

Python

SQL

Delta Lake

Structured Streaming

Airflow

Unity Catalog

GitHub Copilot

Claude

Herramientas

Databricks Workflows

Claude

GitHub Copilot

Unity Catalog

Azure Data Factory

Terraform

Descripción del empleo

AgileEngine is seeking a Middle Data Engineer to modernize a data warehouse into a Databricks Lakehouse. Build batch and streaming pipelines with PySpark and Delta Lake, following a medallion architecture across bronze, silver, and gold layers. AI tools like Claude and GitHub Copilot accelerate development.

You will migrate legacy workloads, implement governance with Unity Catalog, and collaborate with DevOps and analytics teams to ensure performance and data quality at scale.