Job Summary: The Senior Data Analyst is a role within the Department of Finance and Planning, responsible for leading and executing the Corporation’s performance data management, business intelligence, and integrated reporting functions. This role serves as the principal data and analytics resource for collecting, consolidating, validating, and transforming enterprise-wide data into actionable insights, interactive dashboards, and high-quality performance reports that articulate the Corporation’s value creation across the Six Capitals (Financial, Manufactured, Intellectual, Human, Social & Relationship, and Natural). The Officer is tasked with building and maintaining the Corporation’s reporting data infrastructure, automating data pipelines, developing corporate performance dashboards, and producing analytical outputs that support evidence-based decision-making by the Chief Executive Officer, Executive Management, Board of Directors, and Financiers.

Key Responsibilities

(1) Functional Responsibilities

The Officer is responsible for the development, execution, and continuous refinement of the Corporation’s data analytics capabilities, corporate performance reporting systems, business intelligence infrastructure, and data governance frameworks, ensuring data integrity, analytical rigor, and alignment with corporate reporting objectives.

1.1 Integrated Financial Reporting and Corporate Performance Analytics: Lead the collection, consolidation, validation, and analysis of enterprise-wide data from all departments to support the accurate and timely preparation of the Corporation’s Integrated Financial Reports, articulating value creation across the Six Capitals (Financial, Manufactured, Intellectual, Human, Social & Relationship, and Natural). Develop and maintain standardized data collection frameworks, templates, and reporting calendars to ensure consistent, reliable, and auditable data flows from all departmental sources into the corporate performance reporting system. Conduct quantitative analysis of corporate performance data, identifying trends, correlations, anomalies, and leading indicators that inform Executive Management and the Board of Directors on the Corporation’s progress toward its strategic objectives. Support the preparation of the Corporation’s monthly, annual and quarterly performance reports for submission to the relevant statutory institutions, ensuring data accuracy and narrative coherence.

1.2 Business Intelligence and Dashboard Development: Design, build, and maintain interactive corporate performance dashboards and business intelligence solutions using the necessary tools providing real-time or near-real-time visibility into key financial and operational metrics across all departments. Develop automated reporting systems and data pipelines that reduce manual data handling, improve reporting speed, and enhance the accuracy and reliability of corporate performance data. Create tailored analytical views and visual reports for different stakeholder groups (Executive Management, Board of Directors, Departmental Managers, Financiers), ensuring that data is presented in formats that are accessible, actionable, and aligned with each audience’s decision-making needs. Continuously evaluate and improve the Corporation’s business intelligence infrastructure, recommending and implementing enhancements to data visualization, reporting automation, and analytical capabilities.

1.3 Data Governance and Quality Management: Develop and implement the Corporation’s data governance framework, including data quality standards, data ownership protocols, metadata management, and data access policies, ensuring the integrity, consistency, and security of corporate data assets. Establish and enforce data validation, cleansing, and reconciliation procedures across all departmental data sources to ensure the accuracy and completeness of data feeding into corporate reports and dashboards. Maintain comprehensive documentation of data sources, data dictionaries, transformation logic, and reporting methodologies to ensure auditability, reproducibility, and institutional knowledge continuity.

1.4 Financial and Operational Data Analysis: Conduct in-depth analyses of financial and operational data, including revenue trends, cost drivers, production efficiency metrics, supply chain performance, and workforce productivity, providing actionable insights to support strategic and operational decision-making. Perform statistical analyses, predictive modelling, and data mining to identify patterns, forecast trends, and quantify the impact of key business variables on the Corporation’s financial and operational performance. Support the Planning, Strategy and Budgeting Unit and the Capital Budgeting and Analysis Unit by providing validated datasets, analytical outputs, and data visualizations for use in budgeting, forecasting, investment appraisal, and strategic planning processes. Develop and maintain KPI tracking models and performance scorecards that enable Executive Management to monitor progress against targets and take timely corrective action.

1.5 ESG and Non-Financial Data Reporting: Lead the collection, validation, and analysis of Environmental, Social, and Governance (ESG) data, including carbon emissions, energy consumption, water usage, workforce diversity, health and safety metrics, and community engagement indicators, in collaboration with the Department of Quality, Health, Safety and Environment Management. Support the Corporation’s ESG reporting obligations and carbon financing initiatives by providing accurate, verifiable, and timely non-financial data for inclusion in integrated reports, sustainability disclosures, and carbon credit documentation. Develop ESG performance dashboards and tracking tools that enable the Corporation to monitor its environmental and social impact in alignment with its Sustainability and ESG strategy.

1.6 Financial Reporting and Executive  Communication: Prepare and present data-driven analytical reports, dashboard summaries, and performance analytics to the Executive Management, Board of Directors, Board Committees (Audit and Risk Management Committee), and external stakeholders including Financiers. Develop clear, visually compelling executive presentations that translate complex datasets into accessible narratives, highlighting key trends, risks, opportunities, and performance insights. Ensure the accuracy, timeliness, and compliance of all data outputs and analytical reports with applicable regulatory frameworks, including International Financial Reporting Standards (IFRS), Public Finance Management Act (PFMA) requirements, and corporate governance best practices.

1.7 Cross-Functional Data Support: Act as the Corporation’s primary enterprise data analytics resource, providing data extraction, transformation, analysis, and visualization support to all departments for operational, financial, and strategic reporting needs. Collaborate with the Department of Product Development (Information Systems Engineering Division) on data systems integration, ERP data access, and the alignment of operational data architectures with corporate reporting requirements. Coordinate with the Business Analytics Unit within the Department of Marketing and Sales to ensure consistency in analytical methodologies, data definitions, and reporting standards across the Corporation’s analytics functions.

1.8 QHSE Data Intelligence & Integrated Reporting: Lead the design and automation of an integrated QHSE analytics framework to monitor and report on environmental footprint and occupational health. This involves building automated pipelines for metrics like emissions and safety rates, developing interactive ISO-compliance dashboards, and using predictive modeling to mitigate manufacturing risks. These insights ensure high-quality Integrated Reporting on the Corporation’s Natural and Human Capital value creation.

1.9 Any Other Duties: Any other duties assigned by your Supervisor.

(2) Social Responsibilities

The Senior Data Analyst serves as a collaborative and technically credible data and analytics partner, fostering a data-driven culture, building cross-functional data literacy, and contributing to the Corporation’s institutional capacity for evidence-based decision-making.

2.1 Data Literacy and Capacity Building: Serve as a trusted data analytics resource to departmental managers and officers, providing training, guidance, and hands-on support to build data literacy, improve data collection practices, and enhance the quality of departmental reporting across the Corporation.

2.2 Cross-Functional Collaboration: Proactively build and maintain strong working relationships with data owners and reporting focal points across all departments, championing a culture of data accuracy, transparency, and shared accountability for the Corporation’s performance reporting quality.

2.3 Institutional Knowledge Development: Contribute to the development and documentation of the Corporation’s data governance policies, reporting frameworks, dashboard templates, and analytical best practices, ensuring institutional knowledge is captured, standardized, and accessible for continuous improvement and onboarding of future team members.

2.4 Stakeholder Communication Support: Support senior leadership in preparing clear, accurate, and visually compelling data presentations for external stakeholders, including Board presentations, investor briefings, Financier progress reports, and Government submissions, ensuring that the Corporation’s performance narrative is supported by robust, verifiable data.

(3) Emotional Responsibilities:

The role demands attention to detail, technical precision, professional composure, and a deep commitment to data integrity and accuracy, particularly when managing large and complex datasets, operating under tight reporting deadlines, and supporting high-stakes executive and Board-level reporting.

3.1 Analytical Precision and Attention to Detail: Maintain an unwavering commitment to data accuracy, thoroughness, and analytical excellence in all datasets, dashboards, and reports, recognizing that the Corporation’s performance assessments, Board deliberations, stakeholder confidence, and regulatory compliance depend directly on the quality and integrity of the data produced.

3.2 Composure Under Pressure: Demonstrate professional composure, clarity of thought, and effective time management when operating under demanding deadlines particularly during integrated reporting cycles, Board reporting periods, Financier submission timelines, and urgent ad-hoc data requests ensuring consistent output quality without compromising data integrity.

3.3 Integrity and Confidentiality: Handle sensitive corporate performance data, financial datasets, ESG metrics, and Board-level information with absolute discretion, integrity, and professionalism, upholding the highest standards of ethical conduct and data protection responsibility.

3.4 Adaptability and Continuous Learning: Demonstrate the intellectual curiosity and adaptability required to stay current with evolving data analytics technologies, business intelligence platforms, integrated reporting standards, and emerging best practices in data science, corporate performance management, and ESG reporting within the context of a rapidly scaling manufacturing enterprise.

QUALIFICATIONS AND EXPERIENCE

1. Education

• Bachelor’s Degree (Honours) in Statistics or related field from a recognized Academic Institution.
• Master’s Degree in Data Analytics, Statistics, Business Analytics, Information Systems or related field from a recognized Academic Institution.

1. Experience: Applicant should have at least Five (5) Years Experience in development, execution, and continuous refinement of the Business data analytics capabilities, corporate performance reporting systems, business intelligence infrastructure, and data governance frameworks in a reputable Organization preferably in manufacturing.
2. Continuous Professional Development: Certificates in at least Two (2) relevant fields (e.g., Project Management Professional – PMP, Business Intelligence, Data Analytics, Business Strategy, or equivalent certifications).
3. Professional Membership: Affiliate or Associate Membership to a Relevant Professional Body (Institute of Analytics (IoA), Royal Statistical Society (RSS), Alliance for Data Science Professionals, ISDSA, IABAC, DAA, or equivalent) and in Good Standing.

SKILLS AND COMPETENCIES

(1) Data Analytics and Statistical Analysis: Advanced proficiency in statistical analysis, data mining, predictive modelling, and quantitative research techniques, with the ability to extract meaningful patterns, trends, and actionable insights from large, complex, and multi-source datasets. Strong command of analytical and statistical tools with the ability to automate data processing and analytical workflows.

(2) Business Intelligence and Data Visualization: Proficiency in business intelligence and data visualization platforms, particularly Microsoft Power BI, Tableau, or equivalent tools, with demonstrated ability to design, build, and maintain interactive dashboards and automated reporting solutions. Ability to translate complex datasets into clear, visually compelling, and decision-ready analytical outputs tailored to diverse stakeholder audiences (Board, Executive Management, departmental managers, Financiers).

(3) Data Governance and Database Management: Solid understanding of data governance principles, data quality management, metadata standards, and data lifecycle management within a corporate reporting environment.

(4) Environmental Analytics & Carbon Accounting: Proficiency in quantifying “Natural Capital” metrics, including Greenhouse Gas (GHG) emissions, energy intensity per vehicle unit, and waste diversion rates using international standards (e.g., ISO 14064 or GRI).

(5) Occupational Health & Safety (OHS) Metrics: Expertise in calculating and interpreting safety performance indicators such as Lost Time Injury Frequency Rate (LTIFR), Total Recordable Injury Rate (TRIR), and “Near-Miss” trends to drive zero-harm objectives.

(6) Compliance Framework Knowledge: Functional understanding of ISO 9001 (Quality), ISO 14001 (Environment), and ISO 45001 (Health & Safety) management systems to automate compliance monitoring and audit readiness.

(7) Risk Modeling & Root Cause Analysis: Ability to apply statistical methods (e.g., Pareto analysis, Fishbone mapping, or Monte Carlo simulations) to QHSE data to identify manufacturing hazards and predict potential system failures.

(8) Sustainability Reporting: Mastery of integrated reporting principles to translate technical QHSE data into high-level narratives regarding the Corporation’s social and environmental impact for the Board and Financiers.

(9) Reporting, Presentation, and  Communication: Excellent written and verbal communication skills, with the ability to prepare Board-quality data reports, performance dashboards, and executive presentations that translate complex data into accessible, decision-ready narratives for both technical and non-technical audiences. Proficiency in presentation tools and the ability to deliver clear, structured data briefings to senior leadership.

(10) Technology Acumen and Digital Proficiency: Familiarity with Enterprise Resource Planning (ERP) systems and their role as primary data sources for corporate performance reporting within a manufacturing context. Awareness of emerging technologies, including Artificial Intelligence (AI) and Machine Learning (ML) applications in automated reporting, and predictive analytics.

(11) Personal Attributes: Detail-oriented with strong organizational skills and the ability to manage multiple data requests and reporting deadlines simultaneously. High degree of integrity, discretion, and professionalism in handling confidential corporate performance, financial, and ESG data. Self-driven with a strong work ethic, intellectual curiosity, and a commitment to continuous professional development in data science and analytics.

MONTHLY KEY PERFORMANCE INDICATORS (KPIs) FOR THE SENIOR DATA ANALYST AT KIIRA MOTORS CORPORATION

1. Integrated Reporting and Corporate Performance Analytics

1.1 Data Collection and Consolidation

• Data Completeness Rate: Measures the percentage of required departmental data successfully collected, validated, and consolidated within the approved reporting calendar timelines (target: 100% data completeness by the fifth working day of each month).

1.2 Integrated Report Quality:

• Completion rate: Timely production of reports covering all Six Capitals according to the corporate schedule.

2. Business Intelligence and Dashboard Development

2.1 Dashboard Availability and Performance

• Dashboard Uptime: Measures the availability of data for corporate performance dashboards (target: dashboards updated by the fifth working day of each month with zero unplanned downtime).

2.2 Reporting Automation

• Automation Progress: Tracks the number of manual reporting processes converted to automated data pipelines and scheduled reports per quarter, contributing to the Corporation’s digital transformation objectives.

3. Data Governance and Quality

3.1 Data Quality Compliance

• Data Quality Score: Measures compliance with the Corporation’s data governance standards across all departmental data sources, tracking data completeness, accuracy, timeliness, and consistency (target: data quality score of 95% or above).

4. Reporting and Executive Communication

4.1 Report Quality and Timeliness

• Board and Stakeholder Report Timeliness: Tracks the on-time submission of data-driven performance reports, dashboard summaries, and analytical outputs for Board, Board Committee, and Financier review cycles.
• Report Accuracy and Compliance: Measures the accuracy of all analytical reports and data outputs submitted, with zero material misstatements or compliance deficiencies identified per reporting cycle.

5. Cross-Functional Data Support

5.1 Departmental Analytics Support

• Reporting: Tracks the timely completion of cross-departmental data requests, ad-hoc analyses, and analytical support tasks (target: all routine requests fulfilled within 10 working days of receipt).
• Data Literacy Contribution: Tracks the delivery of data training sessions, reporting template improvements, and data quality interventions provided to departmental teams per quarter.

6. QHSE Data Intelligence & Integrated Reporting

• Reporting: Tracks the design and automation of an integrated QHSE analytics framework, including the timely delivery of automated data pipelines (emissions, LTIFR) and interactive ISO-compliance dashboards for Executive Management.
• Compliance & Integration: Tracks the validation of “Natural” and “Human” capital data to ensure 100% alignment between operational records and the Corporation’s Integrated Annual Report, adhering to IIRC standards and sustainability targets.

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