Data Modeler

2 weeks ago

Melbourne, Victoria, Australia Capgemini Full time

About Capgemini

Capgemini is a diverse collective of more than 350,000 strategic and technological experts based across more than 50 countries, partnering with world-renowned clients to transform and manage their businesses. We are dedicated to leveraging cloud, data, AI, connectivity, software, digital engineering, and platforms to address the entire breadth of their business needs. This passion drives a powerful commitment - to unlock the true value of technology.

Over the last 18 months, we have tripled our business in Australia and New Zealand, with over 3,500 team members devoted to helping clients get the future they want. _Now is the time to join our rapidly growing team who are at the forefront of finding new ways technology can help us reimagine what's possible, collecting unique career experiences with global brands and game-changing tech projects.
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Let's talk about the team:
Our Insights and Data team helps our clients make better business decisions by transforming an ocean of data into streams of insight. Our clients are among Australia's top performing companies, and they choose to partner with Capgemini for a very good reason - our exceptional people. Due to continued growth within Capgemini's Insights & Data practice we intend to recruit a Data Modeler with relevant consulting and communication skills. If you are already working in a consultancy role or have excellent client-facing skills gained within large organizations, we would like to discuss our consultant opportunities with you.
**Responsibilities
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Bring thought leadership and experience in uplifting data management practices at the organization
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Act as a thought leader in the technical space through researching and knowing industry trends as well as cutting edge tools and technologies
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Collaborate with stakeholders to understand business requirements and information structures, translating these into comprehensive semantic data models that reflect the underlying relationships and dependencies within the data
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Work and communicate effectively across multiple business and technology teams
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Develop and implement semantic data models that facilitate the integration and interoperability of data across different platforms and systems
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Create and maintain effective mapping, visibility, and traceability between models
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Define business concepts, attributes and relationships and organize them into ontologies, taxonomies, and glossaries
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Design and maintain ontologies, taxonomies, and vocabularies to establish a common understanding and representation of data across the organization
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Evaluate and recommend suitable semantic technologies and tools for data integration, transformation, and scalability ensuring alignment with industry standards and best practices
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Conduct regular assessments and audits of the semantic data models, identifying opportunities for optimization, enhancement, and increased data accessibility
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Provide guidance and support to teams working on data integration projects, ensuring the seamless implementation and adherence to semantic data modelling principles
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Stay updated on emerging trends and advancements in semantic web technologies and data integration practices and integrate relevant innovations into the organization's semantic data model framework
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Recommend and implement design and maintenance standards, guidelines, and procedures.
**Qualification & Soft Skills
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A Bachelor's or Master's degree in management information systems, Computer Science, Computer Information Systems, or a related Information Technology area:

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Proven experience in semantic data modelling, ontology development, and data integration within a complex organizational environment
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In-depth knowledge of semantic web technologies, RDF (Resource Description Framework), OWL(Web Ontology Language), and other relevant standards
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Proficiency in data modelling tools and techniques, with the ability to design and implement effective semantic data models
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Strong analytical, data profiling and problem-solving skills, with the capability to translate complex business requirements into comprehensive semantic data structures
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Familiarity with data management systems, database technologies, and data governance principles
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Excellent oral and written communication and interpersonal skills, enabling effective collaboration with stakeholders at various levels of the organization
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Thorough understanding of modelling methodology and procedures:

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Experience in Finance and Banking industry:

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Desirable AI/ML experience
**#LI-AR1

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