Microsoft Azure Data Services

Specializes in designing, building, implementing, and maintaining our Azure-based data solutions. You will collaborate closely with cross-functional teams to understand data requirements, develop scalable data pipelines, and ensure the reliability, availability, and performance of our data infrastructure.

Here are the key roles and responsibilities for an Azure Data Engineer:

Data Integration and ETL (Extract, Transform, Load):

Design, develop, and deploy scalable data pipelines and ETL processes using Azure Data Factory, Azure Databricks, and other relevant Azure services.These processes extract data from various sources, transform it, and load it into data warehouses or data lakes.

Ensuring efficient data cleaning, conversion, and loading is part of your responsibilities.

Data Management and Storage:

Implement data storage solutions leveraging Azure SQL Database, Azure Cosmos DB, Azure Data Lake Storage, and other Azure data storage technologies.

Your role involves designing data storage systems that scale, perform well, and meet the organization’s requirements.

Big Data and Analytics:

Azure Data Engineers handle and analyze large volumes of data using big data technologies like Azure Databricks and Apache Spark.

You’ll create data processing workflows and pipelines to support data analytics, machine learning, and other data-driven applications.

Monitoring and Troubleshooting:

Develop monitoring and alerting mechanisms to proactively identify and address data pipeline issues.

Monitor data storage and data processing tasks, optimizing performance and troubleshooting any issues that arise.

Conduct performance tuning and optimization of Azure SQL databases and other data processing components.

Optimize data pipelines for performance, reliability, and cost-efficiency, ensuring adherence to best practices and industry standards.

Collaboration and Communication:

Azure Data Engineers work closely with data scientists, business analysts, and other stakeholders.

Collaborate with data scientists and analysts to integrate machine learning models and advanced analytics into data pipelines.

Effective communication skills are essential for understanding business requirements and translating them into technical solutions.

Qualifications:

Bachelor’s degree in Computer Science, Engineering, or a related field. Advanced degree preferred.

Proven experience as a data engineer or similar role, with a strong background in designing and implementing data solutions using Azure services.

In-depth knowledge of Azure Data Factory, Azure Databricks, Azure SQL Database, Azure Cosmos DB, Azure Data Lake Storage, and other Azure data services.

Proficiency in SQL, T-SQL, Python, or other relevant programming languages for data manipulation and scripting.

Experience with data modeling, schema design, and performance tuning in Azure SQL Database.

Strong understanding of data integration techniques, ETL processes, and data warehousing concepts.

Familiarity with data security principles, data governance, and regulatory compliance requirements (e.g., GDPR, HIPAA).

Excellent analytical and problem-solving skills, with the ability to troubleshoot complex data issues and optimize data pipelines for performance and reliability.

Effective communication skills with the ability to collaborate with cross-functional teams and stakeholders.