IT Data & AI Specialist

About the role

Data engineering and platform enablement

• Design, build, and maintain scalable data pipelines and models for analytics and AI use cases.
• Enable reliable, governed data access for business analysts and support integration across ERP, ecommerce, customer data, and other platforms.
• Ensure data quality, consistency, and availability and sustain capabilities for analytics and AI.

AI and generative AI enablement

• Co-develop and operationalize the generative AI onboarding framework.
• Build AI use cases such as automation, copilots, insights generation, and productivity tools.
• Translate business use cases into AI solutions and support evaluation, integration, and deployment under enterprise standards.
• Coordinate with business teams on AI business cases and recommend technical additions.

Governance and business collaboration

• Administer AI onboarding under policy and approval frameworks; support risk, compliance, privacy, and lifecycle governance.
• Collaborate with IT, cybersecurity, legal, and internal control teams on compliance requirements.
• Partner with analysts and stakeholders to prioritize initiatives and co-develop data models, dashboards, and AI use cases aligned with business needs.

Adoption and continuous improvement

• Co-design training, playbooks, and enablement assets; support AI super users and functional champions and drive AI literacy and adoption.
• Identify opportunities for automation, advanced analytics, and AI-driven insights and recommend relevant emerging technologies.
• Measure adoption, business outcomes, and efficiency gains; assist in evaluating AI return on investment and ensure effective data-driven solutions through communication and governance.

Experience and competencies

• Minimum five years' experience in data engineering, including ETL, pipelines, and cloud platforms.
• At least two years' exposure to AI/ML and generative AI tools, such as the Copilot ecosystem.
• Experience translating business stakeholder requirements; understanding of data governance, security, and compliance.
• Strong communication, collaboration, analytical, and problem-solving skills.

Education and technical skills

• Bachelor's degree in Information Technology, Computer Science, Business, or a related field.
• Technical skills listed include Databricks, Microsoft Fabric, Azure Cognitive Services, Azure AI, BigQuery, and GCP.
• AI skills listed include Claude, Copilot, OpenAI, agentic model building such as n8n, vector databases, and Hugging Face.
• Relevant certifications or training in Databricks, Microsoft Fabric, Azure Cognitive Services, Azure AI, or data science platforms.