Business Analyst

Business Analyst - Commercial Analytics Job Snapshot Role: Business Analyst - Commercial Analytics Location: Dubai, United Arab Emirates Industry: Internet Function: Business Analysis-Research Experience: 3-5 years Job Type: Full-time Position Overview Business Analyst - Commercial Analytics in Dubai, United Arab Emirates is an Internet opportunity focused on SQL, business performance analysis, customer behavior, profitability, growth analytics, BI reporting, forecasting, and AI-enabled analytics. talabat is hiring an analytical professional to transform large datasets into commercially relevant insights that support faster, evidence-based decisions across Commercial, Marketing, Operations, Product, and other business functions.

Job DetailsCountry: United Arab Emirates City: Dubai Industry: Internet Function: Business Analysis-Research Salary: 15000-22000 Estimated salary range based on similar jobs in the job city; please confirm the final offer with the employer. Gender: Any Candidate Nationality: Any Job Type: Full-timeRole ContextThe Business Analyst will connect business questions with structured data analysis, helping teams understand what is driving performance and where opportunities or risks are emerging. The position requires strong hands‐on SQL capability combined with commercial judgment, allowing complex analytical findings to be translated into recommendations that stakeholders can act on. A significant part of the role involves improving the efficiency of analytics through generative AI. AI tools will be used to accelerate SQL development, structure analytical approaches, automate repetitive reporting, and improve documentation while maintaining human judgment and rigorous analytical validation.

Key ResponsibilitiesAnalyze business performance across growth, revenue, profitability, customer behavior, marketing, and operational metrics.

Translate loosely defined business questions into structured analytical problems and measurable hypotheses.

Write SQL queries independently to extract, transform, and analyze large datasets.

Optimize SQL queries to improve efficiency, reliability, and analytical turnaround time.

Conduct deep‐dive analyses to uncover performance gaps, emerging trends, growth opportunities, and underlying business drivers.

Evaluate customer acquisition patterns and identify changes in channel or segment performance. Analyze retention, churn, purchase frequency, cohorts, and customer segmentation.

Examine customer lifecycle behavior to identify opportunities for stronger engagement and commercial value.

Support forecasting exercises and scenario modeling for proposed initiatives or business changes.

Develop business cases using data, assumptions, financial drivers, and expected impact. Estimate the potential commercial impact of new products, campaigns, pricing decisions, or operational initiatives.

Build dashboards and recurring reports using suitable business intelligence and visualization platforms.

Improve existing reporting by reducing manual effort and increasing clarity for decision-makers.

Partner with Commercial, Marketing, Operations, Product, and other teams to establish meaningful KPIs.

Challenge unclear metrics and ensure performance measures connect to genuine business outcomes.

Present analytical findings in concise language that non‐technical stakeholders can understand.

Convert data patterns into specific recommendations rather than limiting analysis to descriptive reporting.

Monitor analytical outputs for accuracy, consistency, and reliability.

Validate assumptions and investigate unexpected results before communicating conclusions.

Use generative AI tools to accelerate SQL development, debugging, and query refinement.

Apply AI to generate analytical hypotheses and structure approaches for complex business questions.

Automate repetitive reporting and analytical workflows where appropriate.

Use AI‐supported methods to strengthen documentation and stakeholder communication.

Ensure AI enhances analytical reasoning without replacing independent validation and critical thinking.

Contribute to experimentation analysis, including A‐B testing where applicable.

Support analysis of pricing, retention, churn, marketing efficiency, and unit economics when required.

Ideal ProfileCandidates should bring 3-5 years of experience in Business Analytics, Data Analytics, Strategy Analytics, Growth Analytics, or a closely related discipline. Advanced hands‐on SQL ability is essential. The successful candidate should be comfortable independently querying large datasets, troubleshooting issues, improving query performance, and structuring data for business analysis.

Strong Excel or Google Sheets capability is required, along with practical exposure to BI platforms such as Tableau, Power BI, Looker, Metabase, or comparable v