Senior Databricks Data Engineer — Remote Lakehouse Leader

AgileEngine; Ciudad de México; Presencial; MXN 900.000 - 1.200.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Growth opportunities

Competitive compensation

Remote-friendly

Modern projects

Collaborative culture

Well-being programs

Descripción de la vacante

AgileEngine is seeking a Senior Data Engineer to modernize a 15-year-old data warehouse into a governed Databricks Lakehouse. You will design and operate batch and streaming pipelines using PySpark, Delta Lake, and Databricks Workflows.

You will model medallion architecture and migrate legacy ETL workloads to the Lakehouse, ensuring data parity and minimal disruption, while using AI tools to accelerate development.

Formación

• 4+ years of professional experience in data engineering with Spark and cloud data architectures.
• Strong hands-on experience building data pipelines with Databricks, Spark (PySpark), and Delta Lake.
• Advanced SQL and Python with data modeling 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).

Responsabilidades

• Design, build, and operate batch and streaming data pipelines on Databricks.
• Model and maintain a medallion architecture for analytics and ML consumers.
• Migrate legacy ETL workloads onto the Lakehouse with validated data parity and minimal disruption.
• Use Claude or Github Copilot to accelerate development, write tests, and document solutions.
• Write clean Python and SQL with high-quality tests and documentation.

Conocimientos

Databricks

PySpark

Delta Lake

SQL

Python

Data modeling

Structured Streaming

Airflow

Databricks Workflows

Unity Catalog

dbt

PostgreSQL

Herramientas

Terraform

Azure DevOps

Descripción del empleo

AgileEngine is seeking a Senior Data Engineer to modernize a 15-year-old data warehouse into a governed Databricks Lakehouse. You will design and operate batch and streaming pipelines using PySpark, Delta Lake, and Databricks Workflows.

You will model medallion architecture and migrate legacy ETL workloads to the Lakehouse, ensuring data parity and minimal disruption, while using AI tools to accelerate development.