Data Modeling Specialist

1. Develop the logical data model based on the understanding of the conceptual model and conduct data profiling to deliver high-quality data models and high-quality data within the limits of standards defined by the client, and the industry. 

2. Analyses the requirements and creates a clarification list, if required. 

3. Define data requirements based on an understanding of the same.

4. Create a conceptual model based on the understanding of the business processes. 

5. Map KPIs to the conceptual model, if required Validate the conceptual model with the client Create a logical model (capturing the descriptions of entities, tables, columns, etc.) based on the conceptual model.

6. Create tables and relationships between the tables.

7. Map conceptual to the logical model to ensure the coverage Identify the entities and their properties.

8. Define the attributes and domain (data types).

9. Create a physical model based on functional/ non-functional requirements for small and simple projects.

10. Seek review inputs from the Lead / Manager / Architect on the logical and physical model. Define the data dictionary/ business glossary based on the model developed if required. Define the data governance model to ensure the data quality Interact with SMEs (business) and architects to validate whether the data model is aligned with the technology suggested for the project Interact with the Architect to gather reporting requirements and create models based on the same.

11. Participate in Data Model Health Assessments Create questionnaires, analyse the AS-IS data model for data structure, conformance to industry standards, best practices, and make recommendations for solution/roadmap.

Requirements

1. Ability to coordinate and explain with business users to get the requirements. 

2. Should have very good and clear communication skills. 

3. Should have experience working in an Onsite-offshore model. 

4. 10+ Years of experience in writing complex DB queries in MS SQL Server, Azure Data Models, Power BI, and Azure Analytics Services.

5. Must have 5+ years of minimum experience in developing conceptual, logical, and physical data models, the implementation of RDBMS, operational data store (ODS), data marts, and data lakes on target platforms.

6. Normalization/Denormalization concepts.

7. Metadata management and data governance.

8. Strong Data Analysis and Physical Data Modeling experience.

9. Deep expertise in data modeling and structuring, and experience in high-volume data environments. 

10. Good experience in schema designs and data warehousing ETL/ELT concepts.