Data Engineering And Analytics Lead

Parklane Travels

📍 YAOUNDE - CAMEROON

About the job Role Purpose To design, engineer, and govern the company's enterprise data architecture, ensuring that all operational, financial, fleet, logistics, and digital systems feed into a reliable Single Source of Truth (SSOT). This role transforms fragmented operational data into trusted intelligence, enabling disciplined financial management, operational efficiency, and executive decision-making. The position combines data architecture leadership, systems integration oversight, and analytical governance. Key Responsibilities1. Enterprise Data Architecture & SSOT Ownership - Architect and maintain the company's centralised data environment integrating all core systems. - Design and oversee automated data pipelines across booking, fleet, telematics, CRM, finance, and internal reporting sources. - Define and enforce data models, metric logic, and standardised KPI definitions. - Eliminate parallel reporting and ensure a single, authoritative version of business truth. - Establish structured documentation of all business-critical metrics and data flows. - Ensure controlled access and traceability across datasets. 2. Systems Integration, Reliability & Security - Act as integration authority across Parklane’s technology ecosystem. - Ensure consistent identifiers across assets, routes, branches, drivers, customers, and financial records. - Design synchronisation protocols supporting multi-branch operations, including intermittent connectivity environments. - Supervise backup, recovery, and business continuity procedures. - Enforce access controls and internal data governance standards. 3. Analytics, Forecasting & Decision Assurance - Independently review and interrogate financial models, operational forecasts, and expansion plans. - Conduct structured sensitivity and scenario analysis to identify risk exposure and fragile assumptions. - Maintain executive dashboards derived exclusively from the governed data environment. - Translate analytical findings into clear strategic insights and risk indicators for senior management. - Ensure all published KPIs are consistently defined, auditable, and aligned with approved business logic. 4. Vendor & Digital Product Governance - Serve as the primary technical and data liaison to external vendors and system integrators. - Translate business objectives into structured technical and data requirements. - Validate third-party solutions before acceptance to ensure alignment with enterprise architecture standards. - Oversee data integrity within booking and digital platforms to ensure accurate revenue capture and secure transaction tracking. - Prevent unnecessary system complexity, duplication, or vendor lock-in. - Must-Have Qualifications (Non-Negotiable) Candidates must demonstrate: 1. Data Architecture Competence - Experience designing and governing centralised data environments. - Strong understanding of ETL/ELT concepts, data modeling, and schema design. - Ability to enforce metric standardisation and prevent fragmented reporting. 2. SQL & Data Modeling Proficiency - Strong querying skills. - Ability to design data transformations and validate aggregation logic. - Experience working with structured operational datasets. 3. Governance & Control Mindset - Demonstrated ability to define and enforce data standards. - Comfortable challenging assumptions and inconsistencies across departments. - Structured, disciplined approach to data ownership. 4. Financial & Business Literacy - Ability to interpret financial statements and operational metrics. - Experience reviewing or stress-testing forecasts, budgets, or business models. - Comfort identifying risk drivers and weak assumptions. 5. Multi-System Integration Experience - Experience working within environments involving multiple enterprise systems. - Understanding of APIs, system integrations, and data synchronisation challenges. - Nice-to-Have Qualifications (Valuable but Not Mandatory) - Experience with high-volume operational or telematics data. - Exposure to predictive analytics or advanced forecasting techniques. - Experience supporting marketing analytics or customer lifetime value modeling. - Background in logistics, transportation, or multi-branch operations. - Prior responsibility for enterprise-level data governance frameworks. - Experience managing cloud infrastructure or scalable data platforms. - Formal certifications in data management, analytics, or project delivery. Personal Attributes - High intellectual rigour and structured thinking. - Calm under ambiguity and complexity. - Strong communication skills at executive level. - Comfortable exercising authority in matters of data integrity. - Business-oriented.