Key Skills:AI Foundry (Azure), Azure Synapse, Azure Databricks, Azure Storage, Azurecloud, Azure SQL, Apache Spark, CICD, SQL, Python
Roles and Responsibilities:
- Design and implement end-to-end data architecture solutions on the Microsoft Azure platform.
- Build, optimize, and manage ETL/ELT pipelines for efficient data ingestion, transformation, and processing.
- Collaborate with data engineers, analysts, and business stakeholders to support analytics and reporting requirements.
- Ensure data quality, integrity, governance, and consistency across multiple data sources.
- Architect solutions using Azure services such as Azure Synapse, Azure Databricks, Azure Storage, and Azure SQL.
- Support integration of AI-driven capabilities using Azure AI Foundry where applicable.
- Establish best practices for performance tuning, scalability, cost optimization, and security in Azure data environments.
- Stay updated with evolving Azure technologies and industry best practices in modern data architecture.
Skills Required:
- Strong experience in designing and implementing cloud-based data architectures on Microsoft Azure.
- Proficiency in working with Azure Synapse Analytics, Azure Databricks, and Azure Storage solutions.
- Expertise in building scalable data pipelines and managing large-scale data processing systems.
- Good understanding of Azure SQL and data modeling concepts for enterprise data platforms.
- Familiarity with Apache Spark for distributed data processing is an added advantage.
- Experience with CI/CD practices for deploying and managing data solutions efficiently.
- Working knowledge of Python and SQL for data engineering and transformation tasks.
- Ability to ensure data governance, security, and compliance across cloud data ecosystems.
Education:Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field is preferred.
