Business Intelligence Lead

Role Description

ALU is working to optimize its tech ecosystem and transition from fragmented data sources to a unified, scalable Business Intelligence platform. Reporting to the Senior Manager for Data, the Business Intelligence (BI) Lead will be a key contributor to this technical and operational transformation. This is a hands-on, systems-building role focused on execution rather than basic dashboarding. You will directly oversee the end-to-end implementation and daily operational stability of our data warehouse ecosystem and downstream presentation layers.

In this role, you will be the bridge between technical analytics infrastructure and day-to-day organizational operations. Working alongside platform engineers, data specialists, and data owners, you will be responsible for:

• Architecting the metrics frameworks
• Driving data cataloging
• Partnering with engineering to define robust underlying data pipelines necessary to democratize data across ALU

Your ultimate mission is operational: to establish a self-sustaining, self-service data environment that removes technical bottlenecks and empowers teams across the university with independent, reliable, and frictionless access to actionable data.

Responsibilities

• Project manage and oversee the implementation and maintenance of the data warehouse ecosystem and high-impact, user-friendly dashboard suites (using viz platforms like PowerBI, Apache Superset, AWS Quicksight) tailored for departments across the organization.
• Implement and maintain enterprise data catalogs (e.g., Atlan, Collibra, or open-source alternatives) to map data lineage from source systems to the final BI layer, ensuring complete transparency.
• Partner with cross-functional leadership to establish and maintain a centralized catalog of standardized corporate KPIs, ensuring consistent calculations across all institutional reports.
• Collaborate with the Platform Engineering team and other relevant stakeholders to ensure data models in our data warehouse accurately reflect complex business logic and business definitions.
• Implement automated data profiling and testing frameworks to catch upstream ingestion anomalies before they impact downstream BI deliverables.
• Act as the primary champion for data literacy across ALU. Translate complex analytical concepts for non-technical teams and design "Train-the-Trainer" frameworks to maximize self-service data tool adoption.
• Leverage modern AI-assisted workflows to accelerate report generation, automate report documentation, and extract advanced semantic insights from structured data.
• Other duties as defined by the manager.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field (e.g., Data Analytics, Computer Science, Statistics, Business Administration) or equivalent practical experience.
• Minimum of 5–7 years of experience in a business intelligence or data analytics function, with at least 2 years in a clear team leadership or project ownership role.
• Experience building BI layers directly on top of enterprise applications like Salesforce CRM/SIS, Oracle NetSuite ERP, and Canvas LMS is highly desirable.
• Familiarity with global and regional data privacy standards (e.g., GDPR or local Rwandan/Mauritian data protection laws) is a significant advantage.

Requirements

• Proven track record of architecting and maintaining enterprise-grade data warehouse and analytics environments that drive operational agility and self-service independent data use.
• Practical, hands-on proficiency with cloud data warehousing concepts (AWS Redshift preferred), advanced SQL, and data transformation/modeling frameworks.
• Expert-level mastery of visualization platforms (such as PowerBI, Apache Superset, AWS Quicksight) and strong capability in translating unstructured business requests into clean interface wireframes.
• Superior consultative and interpersonal skills. Ability to collaborate smoothly with cross-functional teams, interrogate ambiguous operational data needs, and translate complex technical architecture into accessible frameworks for non-technical users.
• Thrives in a highly dynamic, fast-paced setting; comfortable building robust frameworks within evolving systems rather than static corporate structures.