Azure Data Engineer - PySpark & Synapse Pipelines

Bluelight Consulting, Llc; Municipio de Profesor Salvador Mazza; A distancia; ARS 1.000.000 - 2.000.000; Jornada completa

Descripción de la vacante

Bluelight Consulting, Llc is seeking an ETL Data Engineer to design, develop, and maintain data integration processes primarily using Python (PySpark) and Azure Synapse Analytics. You will collaborate with data scientists, analysts, and stakeholders to deliver high-quality data for insights in a fast-paced environment.

Responsibilities include building ETL pipelines, optimizing performance, ensuring data quality, and documenting data flows.

Formación

• Bachelor's degree in CS/IT or related field, or equivalent experience.
• Proven ETL data engineering experience using Python (PySpark) for data extraction/transformation/loading.
• Strong SQL skills and experience with Azure Synapse Analytics tools.
• Experience with version control (Git/Azure DevOps) and BI tools like Power BI or Tableau.

Responsabilidades

• Develop and maintain ETL processes using PySpark in Azure Synapse.Notebooks or Pipelines.
• Design data warehouses with star schemas, facts and dimensions for scalable analysis.
• Ingest data from REST APIs, SQL tables, and CSV files and ensure data quality.
• Optimize queries and pipelines to meet SLAs and reliability targets.
• Document data flows, pipelines, and data transformations; collaborate with data teams.

Conocimientos

Analytical thinking

Problem solving

Communication skills

Team collaboration

Educación

Bachelor's degree in CS/IT or related field

Herramientas

Azure Synapse Analytics

PySpark

SQL

Git (Azure DevOps)

Power BI

Tableau

Descripción del empleo

Bluelight Consulting, Llc is seeking an ETL Data Engineer to design, develop, and maintain data integration processes primarily using Python (PySpark) and Azure Synapse Analytics. You will collaborate with data scientists, analysts, and stakeholders to deliver high-quality data for insights in a fast-paced environment.

Responsibilities include building ETL pipelines, optimizing performance, ensuring data quality, and documenting data flows.