Skills Preferred

• Cloud Platforms: Deep understanding of Azure ecosystem, including Azure Data Factory, Data Lake Storage, Blob Storage, power apps, and Functions.
• Additionally, in-depth understanding and implementation of API management such as Apigee.
• Big Data Technologies: Proficiency in Databricks, Spark, PySpark, Scala, and SQL. Data
• Engineering Fundamentals: Expertise in ETL/ELT processes, data pipelines, data modeling, schema design, and data warehousing.
• Programming Languages: Strong Python and SQL skills, with knowledge of other languages like Scala or R beneficial.
• Data Warehousing and Business Intelligence: Strong ERD concepts, designs, and patterns,
• Understanding of OLAP/OLTP systems, performance tuning, Database Server concepts, and BI tools (Power BI, Tableau).
• Data Governance: Strong understanding of RBAC/ABAC, Data Lineage, Data leak prevention, Data security, and compliance.
• Deep understanding and implementation knowledge of audit and monitoring in Cloud.

Experience Preferred

• 7 years of experience applying Enterprise Architecture principles
• 5 years of experience in a lead capacity.
• 5 years of hands-on experience with Azure Data Factory, Azure Databricks, API implementation and management solution, and managing Azure resources.
• 5 years of experience in the following:
• Developing data models and pipelines using Python
• working with Lakehouse platforms
• GitHub CI/CD pipelines and infrastructure automation
• Terraform scripting and with data warehousing systems
• OLAP/OLTP systems and integration of BI tools.
• Bachelor’s degree in an IT-related or Engineering field.