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Data Modeler

LTIMindtree

2 - 5 years

Ghaziabad

Posted: 12/02/2026

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Job Description

LTIMindtree is proud to be an equal opportunity employer. We are committed to equal employment opportunity regardless of race, ethnicity, nationality, gender, gender-identity, gender expression, language, age, sexual orientation, religion, marital status, veteran status, socio-economic status, disability or any other characteristic protected by applicable law.


We are Hiring for Data Modelers!!

Experience: 5 to 12 years

Location: Ghaziabad


Please share your updated resume aditya.utekar2@ltimindtree.com


Primary Skill: Data modeling (conceptual, logical, physical); FSLDM expertise; Data integrity and security;

Performance tuning of data models; Data governance participation; Metadata Management; Teradata database design.


Secondary Skills: Documentation of data models; Mentorship of junior modelers.

Collaboration with analysts and architects; Understanding of OLTP/OLAP systems; Knowledge of ER Modeling Tools like Erwin.


The Senior Data Modeler will design and maintain complex data models for the Insight-client platform, ensuring alignment with enterprise architecture, data governance standards, and performance requirements.


Key Responsibilities:

Responsible for developing and maintaining data models, specifically focusing on the Financial Services Logical Data Model (FSLDM). This role requires extensive experience in data modeling, database management, and a deep understanding of financial services data

Develop, maintain, and optimize conceptual, logical, and physical data models using FSLDM. Establish and enforce data modeling standards and best practices.

Collaborate with architects and developers to ensure model implementation aligns with business needs. Optimize data models for performance and scalability.

Maintain metadata and ensure compliance with data governance standards. Ensure data integrity, stability, and security across all databases.

Work closely with business analysts, data architects, and stakeholders to gather and analyze requirements. Create and maintain comprehensive documentation of data models and their specifications. Participate in data governance processes to ensure data quality and compliance.


Regards,

Aditya Utekar

LTIMindtree

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