Azure Data Engineer

Requirements:

• B2 English level or higher.
• At least 5 years of relevant experience with detailed knowledge of data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools.
• At least 3 years of experience with Azure Cloud portal.
• At least 1 year of hands-on experience with the technologies required to run CKAN installation (Ubuntu, Apache, Nginx, Python, Tomcat/Jetty + Solr and PostgreSQL).
• Experience in deployment of CKAN data management system.
• Proficiency in working with Azure Data Factory - Extraction, Transformation and Loading is required.
• Proficiency in working with Azure Storage/ Data Lake / Data Warehouse is required.
• Experience with Database architecture testing methodology, including execution of test plans, debugging, and testing scripts and tools is required.
• Working knowledge of Azure Synapse analytics is required.
• Strong experience in coding languages like Python, Scala; Java is a plus.
• Experience with Azure DevOps and Azure Purview are a plus.
• Any professional certifications encouraged.
• Masters degree in computer science, Information Systems, Engineering or its equivalent in education and/or work experience.

Scope of Work:

• Collecting large, complex sets of data that meet non-functional and functional business requirements.
• Identifying, designing, and implementing internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes.
• Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using Azure and SQL technologies.
• Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition.
• Working with stakeholders including cloud infrastructure teams, data teams, governance, and information management officers, to collaboratively design, develop and deploy and support data solutions and related infrastructure.