Azure Data Engineer: ETL & PySpark Analytics

Bluelightconsulting; Rosario; A distancia; ARS 61.938.680 - 97.332.212; Jornada completa

Descripción de la vacante

Bluelightconsulting is seeking an ETL Data Engineer to design, develop, and maintain data integration workflows using Python (PySpark) and Azure Synapse Analytics. You will collaborate with data scientists, analysts, and stakeholders to deliver reliable, high‑quality data for analytics in a fast‑paced environment.

Responsibilities include building ETL pipelines, optimizing performance, implementing data quality checks, and ensuring security and governance across data sources such as REST APIs,

Formación

• Bachelor's degree in Computer Science, Information Technology, or related field (or equivalent).
• Proven ETL experience using Python (PySpark) for data extraction, transformation and loading.
• Strong SQL skills (SparkSQL/MS SQL) and data warehousing concepts.
• Experience with Azure Synapse Analytics resources (Notebooks, Pipelines) and data governance.

Responsabilidades

• Develop and maintain ETL data engineering processes using Python (PySpark) within Azure Synapse Analytics Notebooks and Pipelines.
• Design and build data warehouse structures (star schemas, facts, dimensions).
• Extract data from REST APIs, SQL databases, and CSV files.
• Optimize pipelines for performance and reliability to meet SLAs.
• Implement data quality checks and data governance practices.
• Collaborate with data scientists and analysts to deliver analytics-ready data.

Conocimientos

Python

PySpark

Azure Synapse

SQL

REST APIs

Power BI

Tableau

Git

Data Modeling

Data Quality

Educación

Bachelor's degree in Computer Science / Information Technology

Herramientas

Azure Notebooks

Azure Pipelines

Azure Key Vault

Descripción del empleo

Bluelightconsulting is seeking an ETL Data Engineer to design, develop, and maintain data integration workflows using Python (PySpark) and Azure Synapse Analytics. You will collaborate with data scientists, analysts, and stakeholders to deliver reliable, high‑quality data for analytics in a fast‑paced environment.

Responsibilities include building ETL pipelines, optimizing performance, implementing data quality checks, and ensuring security and governance across data sources such as REST APIs,