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Enterprise Data Modelling

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Hybrid

Enterprise Data Modelling

PwC India

Enterprise Data Modelling

Skills

Data AnalysisMachine LearningAISAP ERP

2 months ago

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Important information


Contract type:

Permanent

Location:

Mumbai, Maharashtra, India

Work mode:

Hybrid

Published on:

7 August 2026

What they need


Enterprise Data Modeler

Experience-10-12 Years

Location -Mumbai

Role Overview

We are seeking a seasoned Enterprise Data Modeler to design and govern enterprise-wide data models for banks and financial institutions. The candidate will define conceptual, logical, and physical data models supporting data lakes, data warehouses, regulatory reporting, analytics, AI/ML, and digital transformation initiatives.

Key Responsibilities

Enterprise Data Modelling

  • Develop enterprise conceptual, logical, and physical data models.
  • Define banking data domains such as Customer, Account, Product, Loan, Deposit, Trade Finance, Treasury, Risk, Finance, Collections, and Regulatory Reporting.
  • Establish canonical data models and common business vocabularies.

Data Architecture

  • Design target-state information architecture and data integration strategies.
  • Define subject areas, entities, relationships, and data lineage.
  • Optimize models for reporting, analytics, and operational use cases.

Governance & Metadata Management

  • Create business glossaries, data dictionaries, and stewardship frameworks.
  • Support implementation of data governance and metadata management solutions.
  • Ensure adherence to enterprise architecture standards.

Solution Design

  • Collaborate with business, architecture, analytics, and engineering teams.
  • Support Source-to-Target Mapping (STM), Data Mapping, and ETL design.
  • Enable AI/ML, GenAI, Master Data Management, and API integration initiatives.

Consulting & Leadership

  • Conduct stakeholder workshops and model review sessions.
  • Mentor junior data modelers and architects.
  • Participate in enterprise transformation programs.

Required Skills

  • Strong expertise in enterprise data modelling methodologies.
  • Deep understanding of banking products and processes.
  • Experience with EDW, Data Lake, Data Lakehouse, and MDM implementations.
  • Knowledge of regulatory and risk data models.
  • Familiarity with industry frameworks such as BIAN and BCBS239.

Preferred Tools

  • ERWIN
  • ER/Studio
  • SAP PowerDesigner
  • Collibra
  • Informatica EDC
  • Visio / Enterprise Architect

Key Competencies

  • Data architecture leadership
  • Banking domain expertise
  • Stakeholder engagement
  • Strong documentation skills
  • Strategic thinking

Educational Qualification

  • B.E./B.Tech
  • MBA
  • TOGAF, DAMA-CDMP, BIAN certifications preferred

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