Azure Data Engineer: ETL & Data Warehousing Lead

Bluelightconsulting; Arequipa; A distancia; PEN 204.429 - 306.644; Jornada completa

Descripción de la vacante

Bluelightconsulting is seeking an ETL Data Engineer to design, develop, and maintain data integration pipelines using Python (PySpark) in Azure Synapse Analytics. You will work closely with data scientists and analysts to deliver accurate datasets for decision making.

Responsibilities include data modeling, pipeline optimization, monitoring, and documentation, with emphasis on data quality, security, and governance in a fast-paced environment.

Formación

• Bachelor’s degree or equivalent with data-eng related certs a plus.
• Proven ETL with Python (PySpark) extracting from REST APIs, SQL tables, and CSVs.
• Proficient in Azure Synapse resources (Notebooks, Pipelines, Linked Services, Key Vault).
• Strong SQL (SparkSQL and MS SQL) for extract/transform/load tasks.
• Knowledge of data integration best practices and tooling.
• Experience with version control systems (Git - Azure DevOps).
• Excellent communication and teamwork in fast-paced environments.

Responsabilidades

• Develop and maintain ETL data engineering processes in PySpark within Azure Synapse notebooks/pipelines.
• Design data warehouses with star schemas, facts and dimensions for scalable SWL pools.
• Extract data from REST APIs, SQL tables, and CSV files.
• Optimize data notebooks/pipelines for performance and SLAs.
• Ensure data quality checks and governance compliance.
• Collaborate with data scientists, analysts, and stakeholders.

Conocimientos

Python (PySpark)

SQL queries

Data modeling

Communication skills

Problem-solving

Educación

Bachelor’s degree in Computer Science/IT or related field

Herramientas

Azure Synapse Analytics

Notebooks

Pipelines

Power BI

Git (Azure DevOps)

Descripción del empleo

Bluelightconsulting is seeking an ETL Data Engineer to design, develop, and maintain data integration pipelines using Python (PySpark) in Azure Synapse Analytics. You will work closely with data scientists and analysts to deliver accurate datasets for decision making.

Responsibilities include data modeling, pipeline optimization, monitoring, and documentation, with emphasis on data quality, security, and governance in a fast-paced environment.