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Tata Consultancy Services · Melbourne

Senior Data Modeler

MelbourneSenior individual contributorData & Analytics

Last seen on Tata Consultancy Services’s official careers site on August 1, 2026; it may have closed since.

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Job description

Job Description

Roles and Responsibilities:

Key Responsibilities

  • Analyse and document the current-state customer data ecosystem across staging, integration, and consumption layers.
  • Trace data lineage from source systems through transformation pipelines into customer data marts.
  • Reverse engineer existing BigQuery schemas, transformation logic, and table dependencies.
  • Understand and document how customer attributes, metrics, and business rules are derived.
  • Identify modelling issues, redundancies, duplication, and inefficient data structures.
  • Assess the suitability of current dimensional, denormalized, and analytical data models.
  • Create conceptual, logical, and physical data models for customer domains.
  • Collaborate with business stakeholders, data engineers, analysts, and architects to validate findings.
  • Produce source-to-target mappings and transformation documentation.
  • Recommend target-state modelling approaches including dimensional modelling, wide-table strategies, or domain-oriented designs where appropriate.
  • Support estimation and roadmap development for customer data mart modernization initiatives.
  • Establish traceability between business requirements, customer metrics, and underlying data assets.

Required Experience

  • 8+ years of data modelling and data engineering experience.
  • Strong expertise in customer, CRM, loyalty, marketing, or customer analytics domains.
  • Hands-on experience with Google BigQuery.
  • Proven experience reverse engineering complex data platforms and undocumented environments.
  • Strong understanding of:
  • Data lineage analysis
  • Source-to-target mapping
  • Dimensional modelling
  • Star schemas
  • Denormalized analytical data structures
  • Customer 360 architectures
  • Experience interpreting complex SQL transformation logic.
  • Ability to navigate environments containing hundreds of interconnected tables and datasets.

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