Azure Data Engineer — ETL & Analytics Architect

Bluelightconsulting; Piura; A distancia; PEN 60.000 - 120.000; Jornada completa

Descripción de la vacante

Bluelight is seeking a Data Engineer to develop and maintain ETL data pipelines using Python (PySpark) within Azure Synapse notebooks and pipelines. You will design star schemas and Massively Parallel Processing storage structures, extracting data from REST APIs, SQL databases, and CSV files to ensure scalable analytics.

Your role requires strong SQL skills, familiarity with SparkSQL, and collaboration with data architects to align data models with business needs.

Formación

• Bachelor’s degree in Computer Science, Information Technology, or related field, or equivalent.
• Experience with ETL data engineering using Python (PySpark) for REST APIs, SQL DB tables, and CSV files.
• Proficiency using Azure Synapse resources: Notebooks, Pipelines, Linked Services, and Key Vault.
• Ability to write complex SQL queries, optimize performance, and work with SparkSQL and MS SQL.

Responsabilidades

• Develop and maintain ETL data engineering processes in PySpark within Azure Synapse notebooks/pipelines.
• Design star schemas, facts and dimensions for scalable data storage in an MPP SQL pool.
• Extract data from REST APIs, SQL databases, and CSV files.
• Optimize notebooks/pipelines for performance and scalability.
• Implement data quality checks and data governance practices.

Conocimientos

ETL data engineering

Python (PySpark)

Azure Synapse Analytics

SQL

Data modeling

Data governance

Communication

Educación

Bachelor’s degree in CS/IT or related field

Azure Data Engineer certification a plus

Herramientas

Azure Synapse Notebooks

Azure Synapse Pipelines

Azure Key Vault

SparkSQL / MS SQL

Descripción del empleo

Bluelight is seeking a Data Engineer to develop and maintain ETL data pipelines using Python (PySpark) within Azure Synapse notebooks and pipelines. You will design star schemas and Massively Parallel Processing storage structures, extracting data from REST APIs, SQL databases, and CSV files to ensure scalable analytics.

Your role requires strong SQL skills, familiarity with SparkSQL, and collaboration with data architects to align data models with business needs.