Data Concepts & Data Modelling

Greetings!

Role-Senior Engineer - Azure - Data Specialist (L3)

Required Technical Skill Set

• Data Modelling (Conceptual, Logical, Physical)
• Dimensional Modelling (Star Schema, Snowflake Schema)
• Data Warehouse Design & Architecture
• Fact & Dimension Table Design
• Slowly Changing Dimensions (SCD Type 1 & Type 2)
• Azure Synapse Analytics
• Azure Data Factory (ADF)
• Azure Data Lake Storage Gen2 (ADLS)
• Azure Databricks
• Azure SQL Database
• Advanced SQL & Query Optimization
• ETL/ELT Design and Development
• Data Governance & Data Quality Concepts
• Power BI Data Modelling
• Python/PySpark
• Performance Tuning & Data Optimization

Desired Competencies (Technical/Behavioral Competency) -

• Strong expertise in Data Concepts and Data Modelling.

• Hands-on experience with Azure Synapse, ADF, ADLS, Databricks, and Azure SQL.

• Experience designing and implementing Data Warehouses and Lakehouse solutions.

• Proficiency in Dimensional Modelling, Fact/Dimension tables, and SCD implementation.

• Strong SQL skills including performance tuning, indexing, and optimization.

• Experience building scalable ETL/ELT pipelines.

• Understanding of data governance, data quality, and metadata management.

• Ability to translate business requirements into efficient data models.

• Microsoft Fabric

• Microsoft Purview

• Data Vault Modelling

• Delta Lake and Lakehouse Architecture

• Apache Spark

• Azure Cosmos DB

• Azure DevOps and CI/CD Pipelines

• Terraform/Bicep (Infrastructure as Code)

• Real-time Analytics (Event Hub, Stream Analytics)

• Power BI Advanced Modelling and DAX

• DP-203, DP-600, or AZ-305 certification

Responsibility of / Expectations from the Role-

• Design and maintain conceptual, logical, and physical data models.
• Develop scalable and high-performance Data Warehouse and Lakehouse solutions on Azure.
• Design Fact and Dimension models to support analytics and reporting requirements.
• Build and optimize ETL/ELT processes using Azure Data Factory and Databricks.
• Collaborate with business stakeholders to gather requirements and translate them into data solutions.
• Ensure data quality, governance, security, and compliance standards are met.
• Optimize SQL queries, data models, and data pipelines for performance and scalability.
• Support Power BI and analytics teams with well-structured semantic data models.
• Conduct design reviews and provide technical guidance to junior engineers.
• Drive best practices for data architecture, modelling, and Azure data platform implementation.