Databricks Data Engineer — Lakehouse, PySpark & AI Tools

AgileEngine, LLC.; Medellín; Presencial; COP 289.119.000 - 417.617.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Growth without limits

Competitive compensation

Flexibility: 100% remote

Meaningful, modern projects

Collaborative culture

Well-being & support

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 for analytics and ML workloads.

You will leverage Claude and GitHub Copilot to accelerate development, write robust Python/SQL, and ensure data quality and governance across pipelines.

Formación

• 3+ years of professional experience in data engineering with Spark and cloud data architectures.
• Hands-on experience building data pipelines with Databricks, PySpark, and Delta Lake.
• Advanced SQL and Python with strong data 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 data hygiene during porting.
• Strong problem-solving, collaboration, and communication skills.
• Familiarity with Unity Catalog, data governance, access control, and PII handling.
• Experience with dbt or 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.
• Use Claude or Github Copilot to accelerate development, generate code scaffolding, and review tests.
• 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 with partitioning, clustering, and caching.
• Implement data quality, lineage, and governance using Unity Catalog and automated checks.
• Debug, troubleshoot, and resolve pipeline failures and production incidents.
• Collaborate with DevOps, platform, and analytics engineers on observability, security, and compliance.

Conocimientos

Apache Spark (PySpark)

Delta Lake

SQL

Python

Streaming pipelines

Databricks Workflows

Airflow

Azure Data Factory

Unity Catalog

dbt

KPI data modeling

Herramientas

Databricks

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 for analytics and ML workloads.

You will leverage Claude and GitHub Copilot to accelerate development, write robust Python/SQL, and ensure data quality and governance across pipelines.