Data Engineer II — Cloud Data Pipelines & Analytics

jll; Xalisco; On-site; MXN 450,000 - 900,000; Full time

Job summary

JLL seeks a Data Engineer P2 to design and develop scalable, cloud-based data infrastructure and robust data pipelines in a fast-paced enterprise setting. You will partner with cross-functional teams to identify data requirements, source data, and build efficient ingestion architectures that enable analytics across the organization.

The role focuses on Python, SQL, PySpark, and Databricks within major cloud platforms, with emphasis on data quality, governance, and scalable solutions.

Qualifications

• Bachelor's degree in Computer Science or related field; Master’s preferred.
• 3–5 years of experience in data engineering or full-stack development in cloud environments.

Responsibilities

• Design, develop, and maintain scalable cloud-based data infrastructure using SQL and PySpark.
• Collaborate with cross-functional teams to define data ingestion architecture.
• Design and implement efficient data pipelines to move data to data lakes, warehouses, and analytics platforms.
• Troubleshoot data processing, quality, and pipeline performance issues.
• Stay updated with cloud data engineering trends and best practices.
• Collaborate with data scientists, analysts, and stakeholders to deliver data solutions.
• Document data infrastructure, pipelines, and ETL processes for knowledge transfer.
• Create automated tests and integrate them into testing frameworks.

Skills

Python

SQL

PySpark

Databricks

Data pipelines

Cloud platforms

REST APIs

CI/CD

Education

Bachelor's degree in Computer Science

Master's degree preferred

Tools

Databricks

AWS

Azure

GCP

BigQuery

Snowflake

Job description

JLL seeks a Data Engineer P2 to design and develop scalable, cloud-based data infrastructure and robust data pipelines in a fast-paced enterprise setting. You will partner with cross-functional teams to identify data requirements, source data, and build efficient ingestion architectures that enable analytics across the organization.

The role focuses on Python, SQL, PySpark, and Databricks within major cloud platforms, with emphasis on data quality, governance, and scalable solutions.