Brazil (Remote) · 37d ago
Data Modeler Lead Consultant
Weekday AI · posted Oct 27, 2026
Open to candidates in India
Full-time · Lead
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What this job asks for
Extracted by RemoteHuntMust have
- •8+ years experience
- •3NF Modeling and relational database design
- •Dimensional Modeling (star/snowflake schemas)
- •Data Warehousing concepts
- •Proficiency in SQL
- •Translate business requirements to data models
- •Communication and problem-solving skills
Nice to have
- •Snowflake and cloud data platforms
- •ERWin and ER/Studio
- •Databricks, Microsoft Fabric, SAP
- •ETL/ELT, data integration, metadata, governance
Tools and technologies
SQL, Snowflake, Databricks, Microsoft Fabric, SAP
Read the full posting
This role is for one of Weekday’s clients
Min Experience: 8+ years Location: Remote (India), India JobType: full-time
We are looking for an experienced Data Modeler – Lead Consultant to design, develop, and maintain enterprise-grade data models that support financial reporting, business analytics, and data-driven products. The ideal candidate will have strong expertise in Third Normal Form (3NF) Modeling, Dimensional Modeling, Data Warehousing, and SQL, along with experience in building scalable, reliable, and high-performance data architectures.
In this role, you will collaborate with business stakeholders, data architects, data engineers, analytics teams, and technology leaders to translate complex business requirements into robust data models. You will ensure data consistency, integrity, accessibility, and alignment with enterprise data governance standards. The candidate should bring strong analytical and problem-solving skills, a structured approach to data design, and the ability to lead data modeling initiatives across complex enterprise environments.
Requirements
Key Responsibilities
- Design, develop, and maintain conceptual, logical, and physical data models to support enterprise applications, financial reporting, analytics, and data products.
- Apply 3NF Modeling principles to create normalized relational data structures that minimize redundancy and maintain data integrity.
- Develop dimensional data models, including star and snowflake schemas, facts, dimensions, and hierarchies, to support business intelligence and analytical reporting.
- Design and optimize data warehouse structures to enable efficient data integration, storage, transformation, and retrieval.
- Write, review, and optimize complex SQL queries to validate data models, troubleshoot data issues, and improve query performance.
- Collaborate with business stakeholders to understand functional requirements, reporting needs, and data relationships, translating them into effective modeling solutions.
- Establish and maintain data modeling standards, naming conventions, documentation, metadata, and best practices.
- Work closely with data engineering and ETL/ELT teams to ensure seamless implementation of data models across enterprise data platforms.
- Evaluate existing data architectures, identify gaps, and recommend improvements to scalability, performance, data quality, and maintainability.
- Support data governance, master data management, and data quality initiatives while ensuring consistency across business domains.
- Lead design discussions, conduct model reviews, and provide technical guidance to team members and stakeholders.
Must-Have Skills
- Strong hands-on experience in 3NF Modeling and relational database design .
- Expertise in Dimensional Modeling , including star and snowflake schemas.
- Solid understanding of Data Warehousing concepts, architecture, and implementation.
- Proficiency in SQL, database structures, data relationships, and query optimization.
- Experience translating complex business requirements into scalable enterprise data models.
- Strong communication, stakeholder management, analytical, and problem-solving skills.
Good-to-Have Skills
- Experience with Snowflake and enterprise cloud data platforms.
- Hands-on knowledge of ERWin and ER/Studio data modeling tools.
- Familiarity with Databricks, Microsoft Fabric, and SAP data environments.
- Understanding of ETL/ELT processes, data integration, metadata management, and data governance.
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