Azure PySpark ETL Data Engineer for Scalable Pipelines

Bluelightconsulting; Cuzco; A distancia; PEN 80.000 - 120.000; Jornada completa

Descripción de la vacante

Bluelight is a leading software consultancy delivering innovative technology and exceptional service. We are expanding our data capabilities and seeking an ETL Data Engineer to design, develop, and maintain data integration processes using Python (PySpark) and Azure Synapse Analytics to ensure accurate and available analytical data.

You will collaborate with data scientists and analysts to deliver high-quality data for insights, while maintaining documentation, data quality, and governance

Formación

• Experience in ETL data engineering with PySpark and Python.
• Proficient in Azure Synapse Analytics Notebooks and Pipelines.
• Strong SQL skills (SparkSQL and MS SQL) and data modeling.

Responsabilidades

• Develop and maintain ETL data pipelines using Python (PySpark) in Azure Synapse.
• Design data warehouses with star schemas and scalable structures.
• Extract data from REST APIs, SQL tables, and CSV files.
• Tune performance and monitor ETL jobs to meet SLAs.
• Ensure data quality, governance, and security compliance.
• Document data flows and collaborate with cross-functional teams.
• Support data visualization needs with Power BI or Tableau.

Conocimientos

Python (PySpark)

ETL data engineering

SQL (SparkSQL & MS SQL)

Data integration

Git / Azure DevOps

Big data

Power BI

Tableau

Agile methodologies

Communication

Problem solving

Educación

Bachelor’s degree or equivalent in CS/IT

Herramientas

Azure Synapse Analytics

Descripción del empleo

Bluelight is a leading software consultancy delivering innovative technology and exceptional service. We are expanding our data capabilities and seeking an ETL Data Engineer to design, develop, and maintain data integration processes using Python (PySpark) and Azure Synapse Analytics to ensure accurate and available analytical data.

You will collaborate with data scientists and analysts to deliver high-quality data for insights, while maintaining documentation, data quality, and governance