IT Data & AI Specialist

Role overview

Data engineering and platform enablement

• Design, build, and maintain scalable data pipelines and models for analytics and AI.
• Enable governed analyst access; integrate ERP, ecommerce, customer, and other systems.
• Maintain data quality, consistency, and availability across operational and analytical systems.

AI and governance

• Co-develop and operate generative AI onboarding and support use cases such as automation, copilots, and insights generation.
• Translate business needs into AI solutions and support tool evaluation, integration, and deployment.
• Administer AI policy and approval processes; support risk, compliance, privacy, and lifecycle governance with relevant teams.

Partnership, adoption, and improvement

• Partner with analysts and business teams to prioritize and develop data models, dashboards, and AI use cases.
• Develop AI training, playbooks, and enablement materials; support super users and functional champions.
• Identify new automation and AI opportunities, track emerging technologies, and measure adoption, outcomes, efficiency, and return on investment.

Experience and competencies

• At least five years of data engineering experience, including ETL, pipelines, and cloud platforms.
• Exposure to AI/ML and generative AI tools; experience translating stakeholder requirements; understanding of governance, security, and compliance.
• Strong communication, collaboration, analytical, and problem-solving skills.

Technical skills

• Listed technologies include Databricks, Microsoft Fabric, Azure Cognitive Services, Azure AI, BigQuery, GCP, Claude, Copilot, OpenAI, n8n, vector databases, and Hugging Face.

Education and training

• Bachelor’s degree in information technology, computer science, business, or a related field.
• Relevant certifications or training in named data, Azure, or data science platforms are listed.