Business Analytics Manager

1. Team Leadership & Development

• Recruit, lead, and develop the Business Analytics team
• Set clear goals, conduct performance reviews, and build individual development plans for each team member
• Create a culture of curiosity, data literacy, and continuous improvement within the team
• Mentor team members in coding, AI, and data engineering best practices

1. Analytics Strategy & Architecture

• Define and own the Business Analytics roadmap aligned with the NCC Strategy
• Design NCC’s end-to-end data architecture: ingestion, storage, transformation, and delivery
• Evaluate and adopt best-in-class tools and platforms for data warehousing, BI, and AI analytics
• Establish data governance standards: data quality, lineage, cataloging, and access control

1. AI & RAG System Development

• Lead the design and implementation of AI-powered analytics solutions using LLMs and RAG pipelines
• Build and maintain organizational knowledge bases using vector databases and embedding models
• Develop RAG-based Q&A systems that allow business users to query NCC data in natural language
• Integrate LLM APIs (OpenAI, Azure OpenAI, Anthropic Claude) into internal analytics workflows
• Define AI governance policies including responsible use, output validation, and privacy safeguards

1. Data Engineering & Coding

• Architect and oversee production-grade ETL/ELT pipelines using Python, SQL, and cloud platforms
• Review and approve code written by the team; enforce coding standards, testing, and documentation
• Build reusable data models, APIs, and automated reporting pipelines that scale with NCC’s growth
• Ensure all analytics systems are version-controlled, tested, and deployed through CI/CD workflows

1. Business Intelligence & Insights Delivery

• Own the development of executive dashboards and KPI frameworks across NCC’s departments
• Translate ambiguous business questions into structured analytical problem

Qualifications: Bachelor’s degree (required) in Computer Science, Data Science, Statistics, Information Technology, or a related field Master’s degree in Data Science, Artificial Intelligence, Business Analytics, or MBA (optional) Relevant certifications: Microsoft Azure Data Engineer, AWS ML Specialty, Google Professional Data Engineer, or equivalent (preferred) Minimum 3-5 years of hands-on experience in data analytics, data engineering, or a related field Demonstrated experience building and deploying AI/ML or LLM-based solutions in a production environment Proven track record designing and operating RAG pipelines with vector databases at scale Experience working in hospitality, venue management, events is advantageous