Data Modeler

BriskWin IT Solutions Pvt Ltd; Bengaluru; On-site; INR 900,000 - 1,500,000; Full time

Job summary

BriskWin IT Solutions Pvt Ltd in Bengaluru/Chennai seeks an experienced Data Modeler to design scalable data models and implement Data Vault techniques for an enterprise data lake and lake house.

The role collaborates with data engineers and analysts to translate business requirements into conceptual, logical, and physical models, optimize performance, and ensure security and compliance in Azure environments.

Qualifications

• Experience modeling data across conceptual, logical, and physical layers.
• Hands-on with Data Vault design and implementation.
• Proficient in Azure data services (Azure SQL DB, Data Lake, Synapse).
• Collaborates effectively with data engineers and analysts to derive data requirements.

Responsibilities

• Design and maintain conceptual, logical, and physical data models.
• Create robust data models to support business requirements.
• Collaborate with stakeholders to translate data needs into models.
• Implement best practices for data modeling, including normalization/denormalization.
• Design and implement Data Vault structures (Hubs, Links, Satellites).
• Optimize Data Vault models for performance and scalability.
• Document data models, data flows, and integration processes clearly.

Skills

Data modeling

Data Vault

Azure Data Services

Stakeholder collaboration

Performance optimization

Tools

PowerDesigner

ERWin

ER/Studio

Azure SQL

Azure Data Lake

Azure Synapse

Job description

Exp: 6 years- 12 years

Location: Chennai/Bangalore

Np: Immediate Joiner only

Job Description:

Data Modeling: Design and develop data models to ensure robust, scalable, and flexible data architectures.

Create and maintain conceptual, logical, and physical data models to support business requirements.

Collaborate with stakeholders to understand data requirements and translate them into effective data models. Implement best practices for data modeling, including normalization, denormalization, and data integration.

Data Vault Implementation: Utilize Data Vault techniques to build enterprise data lake and lake house and integrate disparate data sources.

Design and implement Hubs, Links, and Satellites to ensure comprehensive data capture and historical tracking.

Optimize data vault models for performance and scalability.

Cloud Azure: Good to have(Secondary) Design and deploy data models on Azure Data Services, including Azure SQL Database, Azure Data Lake, and Azure Synapse Analytics. Ensure data security, compliance, and best practices in Azure environments.

Collaboration and Communication: Work closely with data engineers, data scientists, and business analysts to understand data needs and ensure data model alignment.

Document data models, data flows, and integration processes clearly and comprehensively. Data Modelling tools Azure:

Data analysis and modeling tools (e.g. Power Designer, ERWin, ER/Studio).