What Jobs are available for Data Visualization in Dubai?

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.

Are you ready to embark on a thrilling adventure as a Senior Business Intelligence Consultant? Join our dynamic team based in Dubai, where you'll have the opportunity to travel the world, partnering with top-tier clients to unlock their data-driven potential.

As a Senior Business Intelligence Consultant, you will be at the forefront of transforming businesses through advanced analytics, data management, and strategic insights. Your expertise in business intelligence and passion for delivering impactful solutions will make you an invaluable asset to our global clientele.

Collaborate closely with clients to understand their business objectives and challenges, and translate them into data-driven solutions.

Conduct in-depth data analysis, employing advanced techniques and tools to extract valuable insights and identify growth opportunities.

Design and develop robust business intelligence solutions, including data models, dashboards, and reports, to provide actionable insights to stakeholders.

Lead end-to-end project implementations, including requirements gathering, solution design, development, testing, and deployment.

Provide strategic guidance and consulting services to clients, advising on best practices, industry trends, and data-driven decision-making strategies.

Conduct workshops, trainings, and knowledge-sharing sessions to empower clients in utilizing business intelligence tools and technologies effectively.

Bachelor's or Master's degree in Computer Science, Data Science, Business Analytics, or a related field.

Minimum of 7 years of experience in business intelligence, data analytics, and consulting roles.

Strong expertise in Data Vault modeling technique, including the ability to design and implement Data Vault structures for scalable and flexible data integration.

Proficient in data visualization tools such as Tableau, Power BI, or QlikView.

Solid understanding of SQL, ETL processes, and data warehousing concepts.

Experience in building and optimizing Data Vault-based data warehouses, including the development of Data Vault models, satellite tables, and hub-link-schema relationships.

Familiarity with automation tools and frameworks for Data Vault modeling and development.

Strong knowledge of advanced analytics techniques, including predictive modeling, statistical analysis, and machine learning.

Proven track record of successfully delivering end-to-end business intelligence projects using Data Vault methodology and driving positive business outcomes.

Excellent communication and presentation skills, with the ability to effectively engage with clients at all levels of the organization.

Flexibility and willingness to travel extensively to client locations worldwide.

We value your expertise in Data Vault modeling technique as it plays a crucial role in our data integration and warehousing strategies. Join our team of talented consultants, and together, we'll revolutionize the way businesses harness the power of data.

Note: Please submit your resume, along with a cover letter detailing your relevant experience and your availability for international travel. Only shortlisted candidates will be contacted for further assessment.

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

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.