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 Optimization

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.

Critical success factors for the Role

58 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.

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 Required

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.

Manager – Data Modelling