What Jobs are available for Business Data in the United Arab Emirates?

Overview

PANGAIA exists to design a future where people and planet reconnect, through every product we create, the stories we tell, and every action we take. We fuse innovation, design, and purpose to responsibly deliver products and experiences that nurture well-being while ensuring minimal collective environmental footprint.

We are a global collective: one heart, many creative minds. From designers to scientists, from storytellers to retailers, we unite to build a platform that brings meaningful innovation to life. We don’t just sell products — we redefine their role: shifting from symbols of consumption to instruments for wellness, consciousness, and lasting positive impact.

Our vision is simple: empower people to live more intelligently, beautifully, and responsibly through purposeful design, cutting-edge innovation, uncompromising quality, and a deeply connected community.

We are seeking a technically skilled and detail-oriented Data & Business Analyst to be a cornerstone in building our data-driven decision-making capability.

PANGAIA is a D2C brand with most sales via its webshop, and we are now planning a significant expansion of our retail activities. Building a strong analytics backbone to support both online and offline businesses is pivotal to provide leadership with a robust data basis for strategic and operational decisions.

In the initial phase, the focus will be on data consistency across systems and departments, implementing a master data concept, and setting up a scalable analytics infrastructure and logic. Once this foundation is in place, the role will evolve into delivering advanced analytics, predictive models, and actionable insights across both e-commerce and retail operations.

• Support the rollout of a master data management concept across all systems (ERP, PLM, CRM, POS, e-commerce).
• Ensure data accuracy, consistency, and availability across D2C and retail channels.
• Design data pipelines that integrate transactional, operational, and customer data.
• Establish governance processes for data ownership, taxonomy, and hierarchy.

• Build dashboards and reports that cover both online and retail performance.
• Provide KPIs and insights for e-commerce (traffic, conversion, AOV, CAC, LTV, returns) and retail (footfall, basket size, sales per sqm, conversion rates).
• Support omni-channel analytics such as customer journey tracking across online and retail touch points.
• Monitor product performance across SKUs, categories, and geographies.

• In coordination with the commercial team on developing demand forecasting models combining internal sales data with external data (seasonality, macroeconomic trends, weather, events).
• In coordination with commercial teams, build predictive analytics for inventory planning, replenishment, and allocation across e-commerce and retail.
• Use AI/ML to create customer segmentation models, churn predictions, and personalized recommendations.
• Continuously refine and validate models to enhance decision-making quality.

• Analyse the full value chain: sourcing, logistics, fulfillment, and returns.
• Provide insights into process efficiency, lead times, and cost optimisation.
• Enable leadership to make informed decisions on pricing, promotions, and assortment strategy.
• Support finance with margin and profitability analytics across sales channels.

• Create analytics frameworks for customer service performance, NPS, and satisfaction tracking.
• Monitor omni-channel customer engagement (CRM campaigns, loyalty programs, retail events).
• Support marketing funnel optimization with data-backed insights.

• Strong command of SQL and experience with data warehouses (Snowflake, Big Query, Azure).
• Programming skills in Python or R for analysis, modelling, and machine learning.
• Experience with ETL/ELT pipelines and data integration tools (dbt, Fivetran, Airflow, Celigo).
• Proficiency with visualisation tools (Power BI, Tableau, Looker).
• Familiarity with cloud environments (Azure, AWS, GCP).
• Understanding of APIs and integrations across ERP, CRM, PLM, POS, and e-commerce platforms.

• Expertise in forecasting, predictive modelling, and machine learning.
• Strong statistical background with ability to apply regression, clustering, time-series analysis, A/B testing.
• Deep knowledge of retail and e-commerce KPIs.
• Ability to create omni-channel analytics frameworks for unified reporting.

• Experience combining online and offline data sets for holistic customer and business insights.
• Familiarity with POS data structures and retail analytics metrics (traffic counters, sales density).
• Knowledge of inventory optimization across multiple distribution channels.
• Understanding of customer behavior analytics both online (clickstream, funnels) and in-store (footfall, dwell time).
• Awareness of sustainability metrics relevant for premium fashion (returns rates, circularity, DPP readiness).

• 3–6 years of experience in data/business analytics, ideally in fashion, retail, or consumer goods.
• Hands-on problem solver with strong analytical rigor.
• Comfortable working in a fast-paced transformation environment.
• Strong communication skills — able to translate technical findings into business impact.
• Curious, proactive, and passionate about creating new capabilities.

At PANGAIA, you will play a pivotal role in building a data-driven culture and a globally recognized responsible fashion brand at scale. You’ll have the chance to work at the intersection of innovation, design, and purpose, creating impact beyond commerce while delivering meaningful returns to shareholders.

By supporting both our e-commerce core and our growing retail footprint, your work will directly shape how we scale international, grow sales and how we optimise operations.

If you are ready to shape the future of responsible fashion and lead one of our most important growth engines, we would love to hear from you.

Overview

PANGAIA exists to design a future where people and planet reconnect, through every product we create, the stories we tell, and every action we take. We fuse innovation, design, and purpose to responsibly deliver products and experiences that nurture well-being while ensuring minimal collective environmental footprint.

We are a global collective: one heart, many creative minds. From designers to scientists, from storytellers to retailers, we unite to build a platform that brings meaningful innovation to life. We don’t just sell products — we redefine their role: shifting from symbols of consumption to instruments for wellness, consciousness, and lasting positive impact.

Our vision is simple: empower people to live more intelligently, beautifully, and responsibly through purposeful design, cutting-edge innovation, uncompromising quality, and a deeply connected community.

We are seeking a technically skilled and detail-oriented Data & Business Analyst to be a cornerstone in building our data-driven decision-making capability.

PANGAIA is a D2C brand with most sales via its webshop, and we are now planning a significant expansion of our retail activities. Building a strong analytics backbone to support both online and offline businesses is pivotal to provide leadership with a robust data basis for strategic and operational decisions.

In the initial phase, the focus will be on data consistency across systems and departments, implementing a master data concept, and setting up a scalable analytics infrastructure and logic. Once this foundation is in place, the role will evolve into delivering advanced analytics, predictive models, and actionable insights across both e-commerce and retail operations.

• Support the rollout of a master data management concept across all systems (ERP, PLM, CRM, POS, e-commerce).
• Ensure data accuracy, consistency, and availability across D2C and retail channels.
• Design data pipelines that integrate transactional, operational, and customer data.
• Establish governance processes for data ownership, taxonomy, and hierarchy.

• Build dashboards and reports that cover both online and retail performance.
• Provide KPIs and insights for e-commerce (traffic, conversion, AOV, CAC, LTV, returns) and retail (footfall, basket size, sales per sqm, conversion rates).
• Support omni-channel analytics such as customer journey tracking across online and retail touch points.
• Monitor product performance across SKUs, categories, and geographies.

• In coordination with the commercial team on developing demand forecasting models combining internal sales data with external data (seasonality, macroeconomic trends, weather, events).
• In coordination with commercial teams, build predictive analytics for inventory planning, replenishment, and allocation across e-commerce and retail.
• Use AI/ML to create customer segmentation models, churn predictions, and personalized recommendations.
• Continuously refine and validate models to enhance decision-making quality.

• Analyse the full value chain: sourcing, logistics, fulfillment, and returns.
• Provide insights into process efficiency, lead times, and cost optimisation.
• Enable leadership to make informed decisions on pricing, promotions, and assortment strategy.
• Support finance with margin and profitability analytics across sales channels.

• Create analytics frameworks for customer service performance, NPS, and satisfaction tracking.
• Monitor omni-channel customer engagement (CRM campaigns, loyalty programs, retail events).
• Support marketing funnel optimization with data-backed insights.

• Strong command of SQL and experience with data warehouses (Snowflake, Big Query, Azure).
• Programming skills in Python or R for analysis, modelling, and machine learning.
• Experience with ETL/ELT pipelines and data integration tools (dbt, Fivetran, Airflow, Celigo).
• Proficiency with visualisation tools (Power BI, Tableau, Looker).
• Familiarity with cloud environments (Azure, AWS, GCP).
• Understanding of APIs and integrations across ERP, CRM, PLM, POS, and e-commerce platforms.

• Expertise in forecasting, predictive modelling, and machine learning.
• Strong statistical background with ability to apply regression, clustering, time-series analysis, A/B testing.
• Deep knowledge of retail and e-commerce KPIs.
• Ability to create omni-channel analytics frameworks for unified reporting.

• Experience combining online and offline data sets for holistic customer and business insights.
• Familiarity with POS data structures and retail analytics metrics (traffic counters, sales density).
• Knowledge of inventory optimization across multiple distribution channels.
• Understanding of customer behavior analytics both online (clickstream, funnels) and in-store (footfall, dwell time).
• Awareness of sustainability metrics relevant for premium fashion (returns rates, circularity, DPP readiness).

• 3–6 years of experience in data/business analytics, ideally in fashion, retail, or consumer goods.
• Hands-on problem solver with strong analytical rigor.
• Comfortable working in a fast-paced transformation environment.
• Strong communication skills — able to translate technical findings into business impact.
• Curious, proactive, and passionate about creating new capabilities.

At PANGAIA, you will play a pivotal role in building a data-driven culture and a globally recognized responsible fashion brand at scale. You’ll have the chance to work at the intersection of innovation, design, and purpose, creating impact beyond commerce while delivering meaningful returns to shareholders.

By supporting both our e-commerce core and our growing retail footprint, your work will directly shape how we scale international, grow sales and how we optimise operations.

If you are ready to shape the future of responsible fashion and lead one of our most important growth engines, we would love to hear from you.

Overview

Job Title: Business Data Analyst (Banking) - Digital Transformation

Job Type: Full-Time Contract (1 year, renewable)

Location: On-site, Dubai, Dubai, United Arab Emirates

Job Summary:

Join our team as a Business Data Analyst at the forefront of digital transformation within a leading UAE bank. In this pivotal role, you will bridge business stakeholders and technology teams, applying deep analytical expertise to drive insights, optimize processes, and elevate customer journeys across key digital banking initiatives. Embrace an asynchronous work culture that values exceptional written communication and proactive problem-solving.

• Elicit, analyze, and document business requirements, user stories, and process flows for digital projects.
• Act as a key liaison between business units and technical teams to ensure clear understanding of project objectives.
• Conduct gap analysis and impact assessments for new features and system changes within core banking functions.
• Participate in Agile/Scrum ceremonies, including sprint planning, backlog grooming, and daily stand-ups.
• Design and execute test scenarios, supporting user acceptance testing (UAT) and solution validation.
• Write complex SQL queries to extract and analyze large datasets, generating actionable insights and KPI reports with Power BI.
• Translate analytical findings into clear, data-driven recommendations and presentations for diverse stakeholders.

• Bachelor’s degree in Computer Science, Engineering, Finance, Business, or a quantitative discipline.
• 5-9 years’ experience as a Business Analyst, with a strong background in Banking, Financial Services, or FinTech.
• High proficiency in SQL and PL/SQL, with hands-on experience in Power BI for data visualization.
• Proven experience working with core-banking systems and exposure to digital transformation projects.
• Solid understanding of Agile methodologies (Scrum, Kanban) and expertise with JIRA.
• Exceptional written communication skills, adept at working in asynchronous, collaborative environments.
• Strong analytical and critical thinking abilities with excellent stakeholder management.

• Relevant professional certifications (CBAP, PMI-PBA, Agile Scrum, Data Analytics).
• Experience with data modeling, Python or R for advanced analytics, and systems like Flexcube or OFSAA.
• Expertise in digital banking products, customer journey mapping, and process optimization.

Become part of our team and contribute to high-impact initiatives, working on projects that set industry standards and drive meaningful change. We foster an inclusive, high-performing culture offering career development opportunities, comprehensive benefits, and a collaborative environment to help you thrive.

Key Responsibilities

Dashboarding & Reporting

• Design, build, and maintain interactive dashboards in Power BI.
• Automate recurring reports and develop self-service analytics tools.
• Ensure data accuracy, consistency, and timeliness.

Data Analysis & Insight Generation

• Analyze trends and performance across channels.
• Identify growth opportunities, margin risks, and operational inefficiencies.
• Support forecasting, budgeting, and strategic planning.

Data Governance & Quality

• Maintain data integrity across multiple sources including ERP, CRM, and vendor portals.
• Support data migration, cleansing, and enrichment initiatives.

Qualifications & Experience:

• Bachelor's degree in Data Science, Business Analytics, Computer Science, or related field.
• 1-3 years of experience in data analysis, preferably within IT or FMCG distribution.
• Advanced proficiency in Power BI, DAX, Tableau etc. data modelling tools.
• Strong Excel skills; experience with SQL, Python, R or other analytics tools is a plus.
• Familiarity with SAP system.

Preferred Attributes:

• Excellent communication and organisational skills with ability to work across teams.
• Experience working with multi-brand, multi-channel datasets.
• Understanding of distribution KPIs.
• Ability to work independently and manage multiple priorities.

Effective Business Decisions Using Data Analysis

ID 257

Course: Effective Business Decisions Using Data Analysis

This interactive, applications-driven 5-day course will highlight the added value that data analytics can offer a professional as a decision support tool in management decision making. It will show the use of data analytics to support strategic initiatives; to inform on policy information; and to direct operational decision making. The course will emphasize applications of data analytics in management practice; focus on the valid interpretation of data analytics findings; and create a clearer understanding of how to integrate quantitative reasoning into management decision making. Exposure to the discipline of data analytics will ultimately promote greater confidence in the use of evidence-based information to support management decision making.

• Discussions on applications of data analytics in management
• The importance of data in data analytics
• Applying data analytical methods through worked examples
• Focusing on management interpretation of statistical evidence
• How to integrate statistical thinking into the work domain

• Explain the scope and structure of data analytics.
• Apply a cross-section of useful data analytics.
• Interpret meaningfully and critically assess statistical evidence.
• Identify relevant applications of data analytics in practice.

• Professionals in management support roles
• Analysts who typically encounter data/analytical information regularly in their work environment
• Those who seek to derive greater decision-making value from data analytics

This course will utilise a variety of proven adult learning techniques to ensure maximum understanding, comprehension, and retention of the information presented. The daily workshops will be highly interactive and participative. This involves regular discussion of applications as well as hands-on exposure to data analytics techniques using Microsoft Excel. Delegates are strongly encouraged to bring and analyse data from their own work domain. This adds greater relevancy to the content. Emphasis is also placed on the valid interpretation of statistical evidence in a management context.

• Day One: Setting the Statistical Scene in Management
  • Introduction; The quantitative landscape in management
  • Thinking statistically about applications in management (identifying KPIs)
  • The integrative elements of data analytics
  • Data: The raw material of data analytics (types, quality, and data preparation)
  • Exploratory data analysis using Excel (pivot tables)
  • Using summary tables and visual displays to profile sample data
• Day Two: Evidence-based Observational Decision Making
  • Numeric descriptors to profile numeric sample data
  • Central and non-central location measures
  • Quantifying dispersion in sample data
  • Examine the distribution of numeric measures (skewness and bimodal)
  • Exploring relationships between numeric descriptors
  • Breakdown analysis of numeric measures
• Day Three: Statistical Decision Making – Drawing Inferences from Sample Data
  • The foundations of statistical inference
  • Quantifying uncertainty in data – the normal probability distribution
  • The importance of sampling in inferential analysis
  • Sampling methods (random-based sampling techniques)
  • Understanding the sampling distribution concept
  • Confidence interval estimation
• Day Four: Statistical Decision Making – Drawing Inferences from Hypotheses Testing
  • The rationale of hypotheses testing
  • The hypothesis testing process and types of errors
  • Single population tests (tests for a single mean)
  • Two independent population tests of means
  • Matched pairs test scenarios
  • Comparing means across multiple populations
• Day Five: Predictive Decision Making - Statistical Modeling and Data Mining
  • Exploiting statistical relationships to build prediction-based models
  • Model building using regression analysis
  • Model building process – the rationale and evaluation of regression models
  • Data mining overview – its evolution
  • Descriptive data mining – applications in management
  • Predictive (goal-directed) data mining – management applications

Data Governance Business Analyst – NDMO

• Interpret and apply NDMO guidelines including data classification.
• Re validate evidence gathered for P1 & P2 NDMO controls and update as applicable.
• Support implementation and validation of P3 NDMO Controls.
• Perform compliance assessment using CAST tool to identify and update all the NDMO controls against evidence gathered and reviewed.
• Ensure organizational data practices comply with national standards and regulatory requirements.
• Support review and enforcement of data governance policies, standards, and procedures across business units.
• Coordinate with risk, compliance, and business teams to ensure governance alignment.
• Act as a liaison between the business and Data Governance Office (DGO) team.
• Facilitate training and onboarding for data stewards and owners across departments.
• Enforce data ownership and accountability structures.
• Engage with business units to identify data ownership and develop domain mapping structures with sign offs.

Virtusa is one of the fastest growing IT Services companies in the Middle East with a growing client base in the UAE, KSA, Qatar & Oman. We work with leading Banking and Financial Services, Travel, Telecom and Enterprise firms in the region, and partner with our clients to achieve recognition from Gartner, IDC, WfMC and other analysts.

Add the Middle East to your global professional experience and have the opportunity to work on some of the leading Digital Transformation programs.

Teamwork, quality of life and professional & personal development are values that Virtusa proudly embodies. By joining us you enter a global team of 30,000+ people who care about your growth, providing exciting projects, opportunities and work with state‑of‑the‑art technologies throughout your career.

Data Analyst-Business Intelligence and Process Automation

University City , United Arab Emirates

Sharjah Performing Arts Academy is seeking a full-time Data Analyst – Business Intelligence and Process Automation.

The Data Analyst plays a key role in supporting evidence-based decision-making by collecting, organizing, analyzing, and presenting statistical and institutional data. The role is responsible not only for preparing reports and insights but also for designing and developing automated data solutions and systems that streamline data collection, integration, and reporting processes. The analyst ensures compliance with Ministry of Higher Education and Scientific Research (MOHESR) requirements, supports accreditation and ranking submissions, and contributes to continuous improvement of data quality and institutional effectiveness.

Reporting to: Senior Manager - Quality Assurance and Strategy

Responsible for: Improvement of data quality

Works Closely with: Senior Manager - Quality Assurance and Strategy

Start Date: 5 January 2026

Employment Type: Full Time

Closing date for applications: 10 November 2025

• Join a talented team in a supportive and collaborative environment
• No unnecessary bureaucracy, no pointless tools, and flexible working hours
• Focus on meaningful work with real responsibilities and autonomy
• Enhance your expertise across diverse aspects of the performing arts industry
• Contribute to creating impactful content that supports our community daily
• Embrace real challenges and responsibilities in a dynamic, rapidly evolving academy