Data Engineer – Senior en PwC Argentina

Design, develop, and maintain scalable data pipelines and systems using Databricks and Python.
Architect and implement data solutions leveraging the Microsoft stack (Azure, SQL Server, etc.).
Collaborate with cross-functional teams to understand business requirements and deliver data-driven insights.
Optimize and enhance data processing capabilities using Docker for containerization.
Ensure data quality, integrity, and security across various systems and platforms.
Troubleshoot and resolve data-related issues in a timely and efficient manner.
Stay updated with the latest industry trends and incorporate best practices into the data engineering processes.
Design, implement, and optimize ETL/ELT workflows using Azure Databricks and Python.
Handle ingestion and transformation of structured, semi-structured, and unstructured data into Azure Data Lake or Synapse Analytics.
Develop scalable solutions for batch and real-time data processing.
Contribute to the architecture of modern data platforms leveraging Azure components such as Azure Data Factory, Data Lake, and Synapse Analytics.
Expertise in SQL for querying and performance tuning.
Familiarity with CI/CD tools like Azure DevOps or GitHub Actions.
Understanding of data governance tools such as Azure Purview.
Knowledge of data visualization tools (e.g., Power BI) is a plus.
Experience with Big Data tools and streaming technologies (Kafka, Event Hub) is desirable

Capacitate