Data Engineer: Spark, Databricks & Azure | Flexible Perks

JobCubby; México; A distancia; MXN 670.000 - 1.116.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Flexible working environment

Volunteer time off

LinkedIn Learning

Employee-Assistance-Program (EAP)

Descripción de la vacante

NielsenIQ is hiring a Data Engineer to join a team using Spark, Scala and PySpark, Databricks, Airflow, and SQL to build and optimize large data pipelines. You will transform data, integrate models, and create scalable infrastructure for analytics delivery.

The role emphasizes hands-on development, CI/CD practices, and collaboration across teams to deliver customer insights and robust data products.

Formación

• Minimum 5-8 years of experience as Data Engineer.
• Experience modeling or manipulating large amounts of data is a must.
• Hands-on experience as a data engineer.
• Highly proficient in using the Spark framework (Python and/or Scala).
• Knowledge of Data Warehousing concepts, strategies, methodologies is good to have.
• Programming experience in Python/Scala, SQL.
• Direct experience building data pipelines using Apache Spark (Databricks/Fabric), Airflow.
• Experience with CI/CD & DevSecOps is a plus.
• Experience with Retail business is a plus.
• Any cloud certification for Data engineer.

Responsabilidades

• Maintaining and assembling data pipelines that process large datasets.
• Runs the complex data transformations needed to generate the facts for clients.
• Integrating finished models into pipelines to build customer insights.
• Use Spark to optimize code (Python/Scala) and improve performance.
• Build infrastructure for ETL with Azure, Databricks and SQL technologies.
• Write and maintain documentation for features and hand off to L2 support.

Conocimientos

Spark

Scala

Pyspark

Python

Airflow

SQL

CI/CD

DevSecOps

AI tools

Herramientas

Databricks

Fabric

Azure

Docker

Kubernetes

Descripción del empleo

NielsenIQ is hiring a Data Engineer to join a team using Spark, Scala and PySpark, Databricks, Airflow, and SQL to build and optimize large data pipelines. You will transform data, integrate models, and create scalable infrastructure for analytics delivery.

The role emphasizes hands-on development, CI/CD practices, and collaboration across teams to deliver customer insights and robust data products.