Azure Data Engineer (8053) at Investec Asset Management

Description of the skill and experience required 

•  Experience: Several years of experience in data engineering and development using Azure technologies.
•  Technical Skills: Expertise in Azure data engineering services such as Azure Data Factory, Azure Databricks, Azure Stream Analytics, and Azure SQL Database. Knowledge of Azure services such as Azure Synapse Analytics, Azure Cosmos DB, and Azure Event Hubs. Proficiency in programming languages such as Python and SQL. 
•  Data Architecture: Experience in designing and implementing data architectures that enable efficient and secure data processing, storage, and analysis in Azure. Knowledge of data warehousing, data lake, and streaming data architectures.
•  Data Integration: Expertise in integrating data from various sources such as on-premises databases, cloud-based systems, and external APIs into Azure data services.
•  Data Transformation: Knowledge of data transformation techniques such as data cleaning, normalization, aggregation, and feature engineering using Azure data services.
•  Data Security: Familiarity with data security and privacy regulations such as POPIA. Ability to implement security measures such as data encryption, access control, and data masking in Azure.
•  DataOps\DevOps: Experience in implementing DevOps\Data Ops practices for Azure data engineering projects. Knowledge of tools such as Azure DevOps & Git.
•  Communication Skills: The ability to communicate technical information to both technical and non-technical stakeholders in a clear and concise manner. Strong presentation and documentation skills.
•  Teamwork: Collaboration with cross-functional teams to identify and prioritize data engineering solutions that meet business objectives. Willingness to learn from and teach others.

Overall, an Azure Data Engineer should have a strong technical background, excellent communication and collaboration skills, and a passion for designing, developing, and implementing efficient and secure data processing solutions using Azure technologies. They should also have a solid understanding of data architecture, integration, transformation, security, and DevOps practices.