SKILLS & EXPERIENCE

• Tertiary qualifications in Computer Science, IT, Data Science, Engineering, or a related field.
• Extensive experience in data architecture, AI, and industry exposure ideally in either a Retail or Manufacturing environment.
• Skilled in cloud platforms (Azure, AWS, GCP), big data tools (e.g., Databricks), and ML frameworks.
• Certified in cloud architecture (e.g., Azure Data Engineer) with hands-on experience in MLOps, CI/CD, and Kubernetes.
• Strong knowledge of data modelling, warehousing, ETL/ELT processes, and data governance.
• Excellent communication, leadership, and problem-solving skills with the ability to influence cross-functional teams.

WE VALUE POTENTIAL AND PASSION

At DuluxGroup, we believe that the right attitude and a willingness to learn can be just as important as meeting every requirement on a job description. If you’re passionate about IT and excited about this role, we encourage you to apply even if you don’t meet all the essential criteria. We value diverse experiences and perspectives, and we are committed to providing opportunities for growth and development.

YOUR ROLE

You will lead the design and implementation of scalable, secure, and high-performance data and AI solutions that drive innovation and business value. With a strong foundation in data architecture, machine learning, and emerging AI technologies, you’ll play a key role in shaping our data and AI strategy. Your ability to engage and influence stakeholders will ensure technical solutions align with strategic goals, while your leadership will foster collaboration and excellence across cross-functional teams.

KEY RESPONSIBILITIES

• Design and implement end-to-end data and AI architectures including data lakes, warehouses, ML pipelines, and real-time analytics platforms.
• Define and enforce architectural standards, best practices, and governance across data and AI systems.
• Evaluate and select technologies for data ingestion, processing, storage, and AI model deployment.
• Collaborate with engineering teams to integrate AI solutions into production environments and ensure data quality, lineage, security, and compliance.
• Provide technical leadership and mentorship to data engineers and scientists.
• Architect scalable ML/AI solutions and guide development across predictive analytics, NLP, and computer vision use cases.
• Engage with stakeholders to translate strategic objectives into technical solutions and communicate complex concepts clearly to non-technical audiences.