On-site Data Engineer 2: Cloud Pipelines & Spark

Jones Lang LaSalle Incorporated; México; A distancia; MXN 600.000 - 900.000; Jornada completa

Descripción de la vacante

Jones Lang LaSalle Incorporated in Jalisco, Mexico is seeking a Data Engineer 2 to design, build, and optimize cloud-based data infrastructure that supports analytics and decision-making across the enterprise.

As part of the Enterprise Data team, you will collaborate with data scientists, analysts, and developers to deliver scalable ETL pipelines, ensure data quality, and implement modern data tooling using PySpark, SQL, and Databricks in a cloud environment.

Formación

• Bachelor's degree in Computer Science, Data Engineering, or related field.
• 3–5 years of data engineering or full-stack development in cloud environments.
• Strong in Python, SQL, PySpark, Spark.
• Experience with Databricks and cloud data warehousing (Redshift/BigQuery/Snowflake).
• Experience with CI/CD and GitHub for automated testing.

Responsabilidades

• Design, develop, and maintain scalable cloud-based data infrastructure using SQL and PySpark.
• Collaborate with cross-functional teams to define data ingestion architecture.
• Build data pipelines from sources to data lakes and warehouses.
• Troubleshoot data processing and pipeline performance.
• Document data architecture and ETL processes.

Conocimientos

Python

SQL

PySpark

Databricks

Big Data

REST APIs

CI/CD

Cloud computing

Educación

Bachelor's degree in Computer Science

Master's degree preferred

Herramientas

Databricks

Spark

BigQuery

Snowflake

AWS

Azure

GCP

CI/CD tools

GitHub

Descripción del empleo

Jones Lang LaSalle Incorporated in Jalisco, Mexico is seeking a Data Engineer 2 to design, build, and optimize cloud-based data infrastructure that supports analytics and decision-making across the enterprise.

As part of the Enterprise Data team, you will collaborate with data scientists, analysts, and developers to deliver scalable ETL pipelines, ensure data quality, and implement modern data tooling using PySpark, SQL, and Databricks in a cloud environment.