Lead Data Architect

ai talent • Australia
Visa Sponsorship
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AI Summary

Design and evolve the enterprise data ecosystem, transitioning from legacy on-premises environments to a high-performance, AI-Ready Modern Data Stack. Define the target state architecture, ensuring data sovereignty and compliance with APRA/Australian regulatory standards. Partner with C-suite stakeholders to develop multi-year strategies that align technical architecture with business ROI and AI/ML adoption.

Key Highlights
Lead the evolution from legacy warehouses to a modern Data Lakehouse
Define the target state architecture, ensuring data sovereignty and compliance
Partner with C-suite stakeholders to develop multi-year strategies
Technical Skills Required
Data Architecture Cloud Data Migrations Snowflake Databricks Microsoft Fabric Advanced SQL Python (PySpark) TOGAF Zachman

Job Description


As the Lead Data Architect, you will be the primary authority for the design and evolution of our client's enterprise data ecosystem; 482 Visa sponsorship is available for the right candidate. This role is "beefed up" to focus on the transition from legacy on-premises environments to a high-performance, AI-Ready Modern Data Stack. You will define the target state architecture, ensuring data sovereignty and compliance with APRA/Australian regulatory standards while enabling advanced analytics at scale.


📋 Core Responsibilities
  • Target State Architecture: Lead the evolution from legacy warehouses to a modern Data Lakehouse (Medallion architecture) using Azure Databricks, Snowflake, or Microsoft Fabric.
  • Data Strategy & Roadmap: Partner with C-suite stakeholders to develop multi-year strategies that align technical architecture with business ROI and AI/ML adoption.
  • Governance & Sovereignty: Architect enterprise frameworks (Collibra/Informatica) to ensure data sovereignty and strict compliance with APRA and banking standards.
  • Advanced Data Modelling: Oversee the design of complex conceptual, logical, and physical models, specializing in Data Vault 2.0 and Star Schema for enterprise-scale analytics.
  • Integration Patterns: Standardize real-time and batch patterns using dbt, Apache Spark, and Kafka.
  • AI-Readiness: Ensure the underlying data fabric is optimized for Large Language Models (LLMs) and predictive analytics.


✅ Technical Requirements
  • Expertise: 10+ years in Data Architecture, with at least 5 years leading high-stakes Cloud Data Migrations.
  • Platform Mastery: Deep expertise in Snowflake, Databricks, or Microsoft Fabric.
  • Languages: Advanced SQL and Python (PySpark) skills.
  • Frameworks: Mastery of TOGAF or Zachman for structured enterprise architecture.
  • Compliance: Proven experience navigating the regulatory landscape of Australian Finance, Government, or Resources.



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