Remote Data Engineer — Databricks Lakehouse & Pipelines

AgileEngine; Bogotá; Presencial; COP 189.167.000 - 283.751.000; 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 a Middle Data Engineer to help modernize a 15-year-old data warehouse into a governed Databricks Lakehouse. You will design batch and streaming pipelines with PySpark and Delta Lake, following a medallion architecture across bronze, silver, and gold layers.

The role involves leveraging AI tools like Claude and Github Copilot to accelerate development. Responsibilities include building scalable data pipelines on Databricks, migrating legacy workloads, and maintaining data

Formación

• 3+ years of professional data engineering experience with Spark and cloud data architectures.
• Hands-on with Databricks, PySpark and Delta Lake.
• Advanced SQL and Python with data modeling skills across dimensional and Lakehouse patterns.
• Experience with streaming ingestion using Structured Streaming, Kafka, or Event Hubs.
• Workflow orchestration with Databricks Workflows, Airflow, or Azure Data Factory.
• Experience with legacy platform migrations, ETL modernization, or data hygiene when porting old systems.
• Familiarity with Unity Catalog and data governance.
• 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 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, documenting and prototyping.
• Write clean, well-tested Python and SQL; maintain high standards through code reviews and docs.
• Optimize Spark jobs and Delta tables for performance and cost (partitioning, clustering, caching, cluster sizing).
• Implement data quality, lineage, and governance with Unity Catalog and automated checks.
• Debug, troubleshoot, and resolve pipeline failures, data defects, and production incidents.
• Collaborate with DevOps, platform, and analytics engineers on observability, security, and compliance.

Conocimientos

Apache Spark (PySpark)

Databricks

Delta Lake

SQL

Python

Structured Streaming

Kafka / Event Hubs

Databricks Workflows

Airflow

Azure Data Factory

Unity Catalog

dbt

Security best practices

Data governance

SQL modeling

Educación

Bachelor's degree in CS/SE

Herramientas

PostgreSQL

Descripción del empleo

AgileEngine is seeking a Middle Data Engineer to help modernize a 15-year-old data warehouse into a governed Databricks Lakehouse. You will design batch and streaming pipelines with PySpark and Delta Lake, following a medallion architecture across bronze, silver, and gold layers.

The role involves leveraging AI tools like Claude and Github Copilot to accelerate development. Responsibilities include building scalable data pipelines on Databricks, migrating legacy workloads, and maintaining data