Data Modeller

Role & responsibilities

Data Modeling

• Design and maintain enterprise-wide conceptual, logical, and physical data models.
• Develop dimensional models including Star Schema and Snowflake Schema for analytics and reporting.
• Define business entities, relationships, hierarchies, metrics, and semantic standards.
• Create canonical data models supporting domain-driven data products.

GCP Data Platform Design

• Design data structures for BigQuery-based analytical platforms.
• Support data modeling across Bronze, Silver, and Gold layers of the Lakehouse architecture.
• Define consumption-ready models for BI, self-service analytics, and AI/ML workloads.
• Collaborate with data architects on enterprise data architecture standards.

Data Governance & Metadata

• Define and maintain data lineage, business glossaries, and metadata standards.
• Work with governance teams to ensure compliance with enterprise data policies.
• Drive master and reference data standardization initiatives.
• Support integration of metadata and lineage capabilities through cloud governance tools
• Data Quality & Integration
• Establish data quality rules and validation frameworks.
• Partner with Data Engineers to map source-to-target transformations.
• Conduct impact analysis for source system changes.
• Ensure consistency across ERP, PLM, CRM, Supplier, Finance, and operational datasets.

Business & Analytics Enablement

• Translate business requirements into scalable data models.
• Enable semantic models for BI and reporting platforms.
• Partner with reporting teams to optimize data structures for analytics consumption.
• Support AI-ready and ML-ready data foundation initiatives.

Required Skills

Data Modeling

• Conceptual, Logical, and Physical Data Modeling
• Dimensional Modeling
• Data Vault Modeling (preferred)
• Star & Snowflake Schema Design
• Normalized and Denormalized Data Structures

Google Cloud Platform

• BigQuery
• Cloud Storage (GCS)
• Dataplex
• LookML / Semantic Layer Design
• Dataflow (understanding)
• Dataproc (understanding)
• Cloud Composer (understanding)

Databases & Querying

• SQL (Advanced)
• Data Warehousing Concepts
• Performance Optimization
• Query Tuning

Governance & Metadata

• Data Lineage
• Data Cataloging
• Metadata Management
• Data Quality Frameworks
• Data Stewardship