Manager - Data Modelling

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Date: 13 Mar 2026

Location: Bangalore, KA, IN, 560024

Company: Tata Consumer Products Limited

Tata Consumer Products Ltd.

 

 

 

 

About the Job: Manager – Data Modelling

 

Function: Digital

Location: Bangalore

Reporting To: Senior Manager – Data Platform Architect

 

At Tata Consumer Products Ltd, we stand #ForBetter – Planet, Sourcing, Nutrition, Communities. And #ForBetter Opportunities …. Here’s an exciting one!

 

How does this Job align to our Strategy?

At the core of Tata Consumer Products' business approach lie six strategic pillars that serve as the foundation for its growth and success: Strengthening & Accelerating our Core Business, Driving Digital and Innovation, Unlocking Synergies, Creating a Future-Ready Organization, Exploring New Opportunities and Embedding Sustainability.

This job opportunity closely aligns with the key strategic pillars of driving digital and innovation and creating a future ready organization.  We are seeking a Data & Semantic Modeller to design, standardise, and govern analytical data models and semantic layers that serve as a trusted foundation for reporting, dashboards, and AI-driven insights. This role focuses on translating raw and curated data into business‑friendly, well‑defined metrics and dimensions, ensuring consistency, clarity, and reusability across the organisation.

You will work closely with data engineers, analytics teams, and business stakeholders to create high‑quality semantic models that enable self‑service analytics and accurate decision‑making at scale.

 

 

 

 

 

 

Top dimensions :

Geography: Global

Direct reports: - NA

Complexity of the role (Optional):

 

 

Matrix Reports : NA

Type of Role : Individual Contributor

Primary Stakeholders (Optional):

What are the Key Deliverables in this role ?

Data Modelling & Analytical Design

  • Design and maintain logical and physical data models optimized for analytics and reporting use cases.
  • Build dimensional models (facts, dimensions) using proven patterns to support scalable, high‑performance analytics.
  • Ensure models are intuitive, extensible, and aligned to common analytical and reporting needs.

Semantic Layer & Metrics Definition

  • Develop and manage semantic models that define standardized business entities, measures, and KPIs.
  • Translate business definitions into consistent, reusable metrics with clear calculation logic.
  • Enable metric reuse across dashboards, reports, and downstream analytical use cases.

Data Quality, Consistency & Governance

  • Enforce modelling standards, naming conventions, and best practices to ensure consistency across datasets.
  • Partner with data engineering teams to validate source data assumptions and transformation logic.
  • Support data quality checks and reconciliation from a modelling and semantic perspective.

Performance & Usability Optimisation

  • Optimize models for query performance, aggregation strategies, and analytical workloads.
  • Balance usability and performance by selecting appropriate modelling techniques and semantic abstractions.
  • Support efficient consumption across BI tools and analytical applications.

Collaboration & Enablement

  • Work closely with business, analytics, and product teams to understand reporting requirements and analytical questions.
  • Act as a bridge between technical data structures and business understanding.
  • Document models, metrics, and definitions to support self‑service analytics and onboarding.

 

 

What are the Critical success factors for the Role ?

  • 5–8 years of experience in data modelling, analytics engineering, or semantic modelling roles.
  • Strong experience designing analytical and dimensional data models for enterprise reporting.
  • Proven ability to translate business requirements into clear, scalable data models and metrics.

What are the Desirable success factors for the Role?

  • Experience working with modern analytics stacks and BI semantic layers.
  • Exposure to AI/ML‑ready data modelling (feature consistency, metric stability).
  • Familiarity with data governance, metadata, and catalog concepts.
  • Experience in consumer, retail, FMCG, or large‑scale enterprise analytics environments.

 

 

Core Technical Skills

 

Area

Requirements

Data Modelling

Strong expertise in dimensional modelling, semantic schemas, and analytical design patterns.

Semantic Modelling

Hands-on experience defining semantic layers, metrics, and business logic for analytics.

SQL

Advanced SQL for validating data, building transformations, and testing model correctness.

Analytics Enablement

Experience supporting BI/reporting use cases with well-documented, trusted models.

Data Quality

Strong understanding of data validation, reconciliation, and consistency checks from a modelling lens.

Collaboration

Ability to work closely with engineers and business stakeholders to align data definitions.

Documentation

Clear documentation of models, metrics, assumptions, and definitions.