Lead Cloud & Data Engineer

Skills

• data modeling
• Spark
• performance tuning
• 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
• PySpark
• Scala
• and SQL. Data Engineering Fundamentals: Expertise in ETL/ELT processes
• data pipelines
• 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
• 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. Infrastructure Deployment: GitHub version control
• CI/CD pipelines
• release management
• Terraform and YAML templates
• and script-based deployments.

Summary