Azure Data Engineer - ETL & Analytics in Synapse

Bluelightconsulting; Ecatepec de Morelos; A distancia; MXN 600.000 - 900.000; Jornada completa

Descripción de la vacante

Bluelight is a leading software consultancy expanding across the Americas. We seek an ETL Data Engineer to design, develop, and maintain data integration pipelines using Python (PySpark) and Azure Synapse, ensuring accurate, high‑quality data for analytics.

You’ll collaborate with data scientists, analysts, and stakeholders in a fast‑paced environment, contributing to data warehousing, data modeling, and data quality initiatives.

Formación

• Experience in ETL data engineering with Python PySpark and Azure Synapse.
• Strong SQL querying, SparkSQL, and MS SQL skills.
• Familiarity with data warehousing concepts, data lakes and cataloging.

Responsabilidades

• Develop and maintain ETL processes using Python (PySpark) in Azure Synapse.
• Design data warehouses with star schemas, facts and dimensions.
• Extract data from REST APIs, SQL databases, and CSV files.
• Optimize notebooks and pipelines for performance and SLAs.
• Implement data quality checks and data governance practices.
• Collaborate with data scientists and analysts on data requirements.
• Document data flows, transformations, and security compliance.

Conocimientos

ETL data engineering

Data modeling

Data quality

Problem solving

Analytical skills

Team collaboration

Educación

Bachelor's degree in CS/IT

Azure Data Engineer certification

Herramientas

Python PySpark

Azure Synapse Analytics

SQL

SparkSQL

MS SQL

Git Azure DevOps

Power BI

Tableau

Descripción del empleo

Bluelight is a leading software consultancy expanding across the Americas. We seek an ETL Data Engineer to design, develop, and maintain data integration pipelines using Python (PySpark) and Azure Synapse, ensuring accurate, high‑quality data for analytics.

You’ll collaborate with data scientists, analysts, and stakeholders in a fast‑paced environment, contributing to data warehousing, data modeling, and data quality initiatives.