• Job Summary:
  The Azure Data Engineer is responsible for designing, developing, and implementing scalable data solutions within the organization’s Azure cloud platform. This role focuses on building high-performance data pipelines, optimizing data storage and retrieval, and ensuring the integrity of data processing. The position requires collaboration with business stakeholders, data scientists, and engineering teams to translate business requirements into technical solutions.

MINIMUM EDUCATION & EXPERIENCE REQUIREMENTS:

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• Hands-on experience with Azure data services, including Azure Data Lake Storage, Azure SQL Database, Azure Data Factory, and Azure Databricks.
• Strong expertise in data engineering, data architecture, and cloud technologies.
• Proficiency in SQL, Python, and PowerShell for data processing and automation.
• Knowledge of data integration techniques, data pipelines, and data warehousing concepts.
• Familiarity with data modeling and schema design principles.
• Understanding of data security and privacy regulations (e.g., GDPR, CCPA).

SPECIAL REQUIREMENTS:

• Azure certifications such as Microsoft Certified: Enterprise Data Engineer Associate are preferred.

KNOWLEDGE, SKILLS, AND ABILITIES:

• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Experience with data partitioning, indexing, and query optimization.
• Ability to document processes and create technical documentation.

• Design, develop, and implement scalable data pipelines and ETL/ELT processes for Azure data storage solutions.
• Automate data pipeline monitoring, error handling, and performance tuning to ensure data integrity.
• Optimize data storage and retrieval mechanisms for efficient processing of large datasets.
• Develop and maintain data models and schemas to support analytics and reporting.
• Implement data security and privacy measures to comply with industry regulations.
• Manage data ingestion from multiple sources, including APIs, databases, and streaming platforms.
• Perform data quality checks and validation procedures to maintain accuracy and consistency.
• Implement transformation and enrichment processes using Azure Data Factory, Azure Databricks, and related tools.
• Document technical designs, deployment processes, and best practices for data engineering solutions.
• Collaborate with DevOps teams for deployment and management of Azure-based data solutions.
• Work with data scientists to operationalize and deploy machine learning models on Azure.