Databricks Data Engineer — Lakehouse Pipelines & AI Tools

AgileEngine; Almoloya de Juárez; Presencial; MXN 480.000 - 720.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Growth budget

Competitive pay

Remote work

Modern projects

Collaborative culture

Well-being support

Descripción de la vacante

AgileEngine invites 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 across bronze, silver, and gold layers.

Join a team using Claude and GitHub Copilot to speed development, write clean Python and SQL, optimize Spark jobs, implement data quality and governance, and collaborate across DevOps, platform, and analytics teams.

Formación

• 3+ years of professional experience in data engineering.
• Strong hands-on experience with Databricks, Apache Spark (PySpark), and Delta Lake.
• Advanced SQL and Python skills with data modelling expertise.

Responsabilidades

• Design, build, and operate batch and streaming data pipelines on Databricks using PySpark, Delta Lake, and Databricks Workflows.
• Migrate legacy ETL and data warehouse workloads onto the Lakehouse with validated data parity.
• Collaborate with DevOps, platform, and analytics engineers on observability, security, and governance.

Conocimientos

Data engineering

Spark / PySpark

SQL

Python

Data modelling

Cloud data architecture

Problem solving

Communication

Unity Catalog

dbt

Herramientas

Databricks

Delta Lake

Apache Spark

dbt

Airflow

Azure Data Factory

Terraform

Dynatrace

Descripción del empleo

AgileEngine invites 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 across bronze, silver, and gold layers.

Join a team using Claude and GitHub Copilot to speed development, write clean Python and SQL, optimize Spark jobs, implement data quality and governance, and collaborate across DevOps, platform, and analytics teams.