Data Analyst jobs
- ASICAustralia
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- EnervenHindmarsh SA
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- City of SydneySydney NSW
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- HUB24Sydney NSW
- Contribute to data quality, validation, governance and secure data-handling practices.
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- IKEALogan City QLD
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- Department of Education and TrainingDarwin NT
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- LovisaHawthorn VIC 3122
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- LovisaHawthorn VIC 3122
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- University of SydneyAustralia
- Demonstrated experience identifying data quality issues, gaps and trends and developing practical recommendations.
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- Blacktown City CouncilBlacktown NSW
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- NorthcottNorth Parramatta NSW 2151
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- ASICAustralia
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- Berry StreetMelbourne VIC
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This job has expired on Indeed
Analysis Lead – Data & AI Accelerated Modernization for AI
Analysis Lead – Data & AI Accelerated Modernization for AI
Job details
Full job description
Role Title: Analysis Lead – Data & AI Accelerated Modernization for AI
Description: The Analysis Lead – Data & AI Accelerated Modernization for AI is responsible for driving analysis across initiatives that simplify, modernise, and intelligently automate the organisation’s data landscape. The role leverages AI-assisted analysis, automated lineage discovery, and GenAI-driven insights to streamline data flows, reduce duplication, and improve data accessibility.
This leader works at the intersection of data, AI, and business transformation — shaping the target-state data ecosystem, accelerating simplification with intelligent tooling, and ensuring analysis outputs power next-generation AI and analytics capabilities.
Key Responsibilities:
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Lead a team of Data Engineers, GenAI practitioners and Business/Data/AI Analysts delivering analysis for data transformation and AI-enabled modernisation initiatives.
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Define analysis strategy that incorporates AI-driven insights, automated metadata discovery, and LLM-assisted documentation. Ensure analysis outputs align with enterprise data, AI, and architecture standards.
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Use Agentic AI-enabled tools for automated lineage mapping, metadata extraction, data quality scanning, and pattern detection.
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Identify high-value simplification opportunities using data profiling augmented by LLMs and machine learning (e.g., duplication detection, data dependency clustering).
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Partner with data engineers and GenAI practitioners / data scientists to ensure simplified data flows enable future GenAI models, agentic workflows, and automation solutions.
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Produce clear, AI-assisted artefacts including lineage maps, canonical models, semantic layer requirements, and data dependency diagrams.
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Define functional and non-functional requirements for GenAI-powered data products, data transformation pipelines, and automation capabilities.
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Facilitate workshops by combining traditional BA discovery techniques with AI-driven insights to accelerate decision-making.
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Communicate complex GenAI and data concepts to non-technical stakeholders, translating them into actionable roadmaps. Present analysis findings, trends, and AI-generated insights to senior leadership and governance forums.
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Integrate LLM powered data governance practices, including automated validation of data definitions and business rules. Implement continuous analysis automation using LLM-based agents for traceability, documentation upkeep, and impact assessment.
Key Skills:
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12+ years in Business/Data Analysis with experience leading complex data transformation or simplification programs.
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Experience in enterprise cloud environments (AWS, Azure, GCP), particularly with AI-native services and LLMs services.
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Strong understanding of data modelling, domain design, metadata management, and analytic architectures.
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Hands-on experience with Agentic AI/ML or GenAI tools used for analysis, lineage, profiling, or documentation. Ability to translate Agentic AI opportunities into actionable simplification outcomes.
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Excellent communication, facilitation, storytelling, and stakeholder engagement capabilities.
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Experience with AI-driven data platforms, vector databases, feature stores, and semantic layers is a plus.
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Familiarity with data governance frameworks enhanced by GenAI automation and AI agents.
Qualifications
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Bachelor’s in Data, AI, Information Systems, Computer Science, or related field.
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Certifications in Business Analysis (CBAP), Data Management (DAMA), Agile frameworks, or Agentic AI/ML fundamentals is a plus.
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