Enterprise Data Architect

6 days ago

Melbourne, Victoria, Australia Bebeedatastrategist Full time

About the Role
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We're seeking a visionary leader to spearhead an enterprise-wide data strategy, focusing on embedding AI capabilities across the organisation.
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As the head of data architecture, governance, and analytics, you'll ensure data is leveraged as a strategic asset—driving innovation, operational efficiency, and competitive advantage.
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Key Responsibilities:
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Design and implement modern data architectures, including data lakes, warehouses, master data management, and real-time data pipelines
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Develop and execute a comprehensive data and AI strategy aligned with business objectives
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Establish and uphold robust data governance frameworks, policies, and standards
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Partner with business and technology leaders to identify high-impact opportunities that maximise the value of organisational data
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Drive adoption of AI/ML technologies to enhance decision-making, automation, and customer experience
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Lead and grow a high-performing team of data engineers, scientists, and analysts
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Oversee the development of data products and services that support operations and innovation
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Ensure compliance with data privacy, security, and regulatory requirements
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Champion a data-first culture through education, advocacy, and community leadership
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Stay ahead of emerging technologies and trends in AI, data platforms, and analytics
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About You
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You're a strategic leader with a passion for data and AI, and a proven track record of building high-performing teams. You combine deep technical expertise with the ability to drive enterprise-wide transformation.
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Requirements:
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A Bachelor's degree in Computer Science or a related field, or 10–15 years of experience in senior data leadership roles
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Strong foundation in data architecture, engineering, and governance
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Demonstrated success leading enterprise data and analytics functions, including AI/ML initiatives
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Experience managing cross-functional teams and driving cultural change
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Familiarity with cloud-based data platforms and hybrid environments
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Deep understanding of AI/ML technologies and their business applications
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Exceptional leadership and stakeholder engagement skills
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Ability to translate complex data concepts into clear business value
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Outstanding communication and presentation skills, including with C-suite stakeholders
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