We are seeking a highly skilled Azure Data Engineering Consultant to join our data team and drive the development and optimization of enterprise-grade data solutions. The ideal candidate will have extensive experience in enterprise ETL, strong SQL skills, and a solid background in Azure-based data engineering. Proficiency in either Python or Spark SQL is essential to succeed in this role.
Design, develop, and optimize scalable ETL pipelines and data workflows in Azure.
Implement and maintain data integration processes using Azure Data Factory, Azure Synapse, and other Azure-native tools.
Write complex SQL queries for data extraction, transformation, and analysis in large-scale enterprise environments.
Build and manage data models and data lake architectures.
Leverage Python or Spark SQL for data processing, transformation, and analysis tasks.
Collaborate with stakeholders, data analysts, and other engineering teams to define data requirements and deliver high-quality data products.
Ensure security, compliance, and performance optimization across data solutions.
Proven enterprise-level ETL and data engineering experience using SQL.
Strong hands-on experience with Microsoft Azure data services (e.g., Azure Data Factory, Azure Synapse Analytics, Azure Data Lake).
Proficiency in Python or Spark SQL for data engineering workflows.
Experience with modern data architecture, including data lakes, warehouses, and real-time processing.
Familiarity with CI/CD practices and infrastructure-as-code in a cloud environment is a plus.
Excellent communication and documentation skills.
Azure certifications (e.g., Azure Data Engineer Associate) are highly desirable.
Experience with Databricks, Delta Lake, or similar platforms.
Knowledge of data governance, security best practices, and regulatory compliance (GDPR, HIPAA, etc.).
