Data Engineer: Databricks Lakehouse & PySpark/Delta - Remote

INGEPSY; Risaralda; Presencial; COP 78.120.000 - 122.760.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Growth opportunities

Competitive pay

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 Databricks Lakehouse. You will build batch and streaming pipelines with PySpark/Delta Lake, following a medallion architecture for analytics and ML use cases.

You will work with Claude and GitHub Copilot to accelerate development, write clean Python and SQL, and optimize Spark jobs for performance and cost. This remote role offers flexible hours and collaboration with global teams.

Formación

• 3+ years of professional data engineering experience with Spark and cloud data architectures.
• Hands-on experience building data pipelines with Databricks, Spark (PySpark), and Delta Lake.
• Advanced SQL and Python with data modeling in 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 during porting.
• Familiarity with Unity Catalog, data governance, access control, and PII handling.
• Experience with dbt or equivalent transformation frameworks.
• Secure coding practices and 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 for analytics, reporting, and ML consumers.
• Migrate legacy ETL and data warehouse workloads onto the Lakehouse with data parity and minimal disruption.
• Leverage Claude or GitHub Copilot to accelerate development with scaffolding, tests, docs, and prototyping.
• Write clean, well-tested Python and SQL; ensure quality through code reviews and documentation.
• Optimize Spark jobs and Delta tables for performance and cost via partitioning, clustering, caching, and sizing.
• Implement data quality, lineage, governance, Unity Catalog, and automated validation 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

Databricks

SQL

Python

Structured Streaming

Kafka

Airflow

Databricks Workflows

Unity Catalog

dbt

Broaden Lakehouse

Herramientas

Databricks

Azure Data Factory

Unity Catalog

dbt

Descripción del empleo

AgileEngine is seeking a Middle Data Engineer to modernize a 15-year-old data warehouse into a Databricks Lakehouse. You will build batch and streaming pipelines with PySpark/Delta Lake, following a medallion architecture for analytics and ML use cases.

You will work with Claude and GitHub Copilot to accelerate development, write clean Python and SQL, and optimize Spark jobs for performance and cost. This remote role offers flexible hours and collaboration with global teams.