Senior Data & Insights Analyst

Al Tayer Group; Dubai; On-site; AED 300,000 - 540,000; Full time

Job summary

Al Tayer Group is building a dedicated business-facing analytics capability to convert enterprise data into clear, actionable insight. You will partner with business leaders to understand priorities and use fact-based analysis to improve decisions and outcomes, beyond reporting.

Role focuses on defining trusted performance measures, dashboards, and analytics products across Motors, Retail and Group data aligned to real business needs and adoption.

Qualifications

• 5+ years in business analytics with stakeholder engagement.
• Strong business analysis and consulting skills with understanding of strategy, processes and commercial drivers.
• Ability to convert ambiguous questions into structured analyses and actionable recommendations.
• Strong KPI design, performance measurement, metric governance and value-realisation tracking.
• Advanced trend, variance, driver, exception, segmentation, funnel, cohort, scenario and root-cause analysis.
• Strong data visualisation and storytelling for executive and operational audiences.
• Hands-on Power BI and Excel; working knowledge of SAC, Data Analyzer and Datasphere is preferred.
• Working knowledge of SQL, dimensional models, semantic layers, data quality and lineage is advantageous.
• Ability to challenge assumptions, distinguish correlation from causation and communicate limitations.
• Strong facilitation, stakeholder management, presentation, writing and influencing skills.
• Experience with Agile analytics delivery, requirements, UAT, adoption and product lifecycle management.

Responsibilities

• Build trusted relationships with business leaders and act as the primary analytics partner for assigned functions or business units.
• Translate strategic priorities, business questions and performance challenges into a focused analytics and insight agenda.
• Define, standardise and socialise enterprise and domain KPIs, measures, targets and business definitions with clear ownership.
• Shift analytics conversations from report delivery to decisions, outcomes, actions and value realisation.
• Align SAC, Power BI, Datasphere and modern data platform investments to priority business use cases and measurable outcomes.
• Strengthen ways of working across Business, BI, Data Engineering, Data Governance and AI teams.
• Improve data literacy, interpretation of measures and confidence in evidence-based decisions.
• Understand stakeholder objectives, processes, pain points, opportunities, decisions and information needs.
• Frame business problems into testable analytical questions, hypotheses, measures and decision criteria.
• Develop KPI definitions covering purpose, formula, grain, dimensions, source, frequency, owner, target, thresholds and interpretation.
• Maintain KPI catalogues, insight briefs and traceability from business outcomes to data and BI products.
• Analyse performance to identify patterns, trends, drivers, exceptions, correlations, risks and opportunities.
• Explain what changed, why it changed, where attention is required and what actions should be considered.
• Develop executive insight packs, management commentary, performance narratives and decision-support materials.
• Perform segmentation, variance, contribution, cohort, funnel, scenario and root-cause analysis where relevant.
• Shape dashboards, stories, semantic models and self-service experiences with BI specialists.
• Clarify source requirements, transformation logic, granularity and consumption needs with Data Engineering and Datasphere teams.
• Resolve definition conflicts, quality issues and ownership gaps with Data Governance and data owners.
• Identify use cases requiring forecasting, prediction, optimisation or intelligent automation with AI teams.
• Validate analytical outputs and document assumptions, limitations and reconciliation results.
• Facilitate requirements workshops, KPI design, insight reviews, demonstrations, UAT and business sign-off.
• Create adoption plans, user guidance, training and office-hour support for SAC, Power BI and self-service analytics.
• Monitor usage, feedback, decision impact and realised value; recommend enhancement, consolidation or retirement.
• Prioritise the analytics demand backlog by strategic value, urgency, feasibility, data readiness and reuse potential.
• Protect confidential information and apply role-based access, responsible analytics and governance standards.

Skills

KPI design

Data visualization

Stakeholder management

Power BI

Excel

SQL

Agile analytics

Data governance

Analytics storytelling

Education

Bachelor's degree

Certification in business analysis

Certification in Power BI

Certification in SAP Analytics Cloud

Tools

Power BI

SAC

Datasphere

Data Analyzer

Excel

Job description

Establish a dedicated business-facing analytics capability that converts enterprise data into clear, actionable insight. Partner with business leaders to understand strategic priorities, challenges and opportunities, then use fact-based analysis to improve decisions and measurable business outcomes.

Go beyond reporting by defining trusted performance measures, identifying trends, drivers, exceptions, risks and opportunities, and ensuring analytics products across Motors, Retail and Group Business data are aligned to real business needs and adopted effectively.

Essential Roles and Responsibilities

Strategic Roles and Responsibilities

• Build trusted relationships with business leaders and act as the primary analytics partner for assigned functions or business units.
• Translate strategic priorities, business questions and performance challenges into a focused analytics and insight agenda.
• Define, standardise and socialise enterprise and domain KPIs, measures, targets and business definitions with clear ownership.
• Shift analytics conversations from report delivery to decisions, outcomes, actions and value realisation.
• Align SAC, Power BI, Datasphere and modern data platform investments to priority business use cases and measurable outcomes.
• Strengthen ways of working across Business, BI, Data Engineering, Data Governance and AI teams.
• Improve data literacy, interpretation of measures and confidence in evidence-based decisions.

Functional Roles and Responsibilities

• Understand stakeholder objectives, processes, pain points, opportunities, decisions and information needs.
• Frame business problems into testable analytical questions, hypotheses, measures and decision criteria.
• Develop KPI definitions covering purpose, formula, grain, dimensions, source, frequency, owner, target, thresholds and interpretation.
• Maintain KPI catalogues, insight briefs and traceability from business outcomes to data and BI products.
• Analyse performance to identify patterns, trends, drivers, exceptions, correlations, risks and opportunities.
• Explain what changed, why it changed, where attention is required and what actions should be considered.
• Develop executive insight packs, management commentary, performance narratives and decision-support materials.
• Perform segmentation, variance, contribution, cohort, funnel, scenario and root-cause analysis where relevant.
• Shape dashboards, stories, semantic models and self-service experiences with BI specialists.
• Clarify source requirements, transformation logic, granularity and consumption needs with Data Engineering and Datasphere teams.
• Resolve definition conflicts, quality issues and ownership gaps with Data Governance and data owners.
• Identify use cases requiring forecasting, prediction, optimisation or intelligent automation with AI teams.
• Validate analytical outputs and document assumptions, limitations and reconciliation results.
• Facilitate requirements workshops, KPI design, insight reviews, demonstrations, UAT and business sign-off.
• Create adoption plans, user guidance, training and office-hour support for SAC, Power BI and self-service analytics.
• Monitor usage, feedback, decision impact and realised value; recommend enhancement, consolidation or retirement.
• Prioritise the analytics demand backlog by strategic value, urgency, feasibility, data readiness and reuse potential.
• Protect confidential information and apply role-based access, responsible analytics and governance standards.

Job Requirements

Education/Certification and Continued Education

• Bachelor's degree in Business, Economics, Finance, Statistics, Data Analytics, Information Systems, Engineering or a related discipline.
• Certification in business analysis, data analytics, Power BI, SAP Analytics Cloud or a relevant domain is preferred.
• Continued learning in analytical methods, data storytelling, decision science and responsible AI is advantageous.

Years of Experience

5+ years in business analytics, insights, management information, business intelligence or performance management, including significant business-facing stakeholder engagement.

Knowledge and Skills

• Strong business analysis and consulting skills with understanding of strategy, processes and commercial drivers.
• Ability to convert ambiguous questions into structured analyses and actionable recommendations.
• Strong KPI design, performance measurement, metric governance and value-realisation tracking.
• Advanced trend, variance, driver, exception, segmentation, funnel, cohort, scenario and root-cause analysis.
• Strong data visualisation and storytelling for executive and operational audiences.
• Hands-on Power BI and Excel; working knowledge of SAC, Data Analyzer and Datasphere is preferred.
• Working knowledge of SQL, dimensional models, semantic layers, data quality and lineage is advantageous.
• Ability to challenge assumptions, distinguish correlation from causation and communicate limitations.
• Strong facilitation, stakeholder management, presentation, writing and influencing skills.
• Experience with Agile analytics delivery, requirements, UAT, adoption and product lifecycle management.