7 Data Management jobs in Dubai

Overview

Digital Strategy and Data consultant will collaborate with multiple business and IT stakeholders within the target enterprise. Digital strategy and Data consultants are expected to create very good relationships with the client in order to ensure building trust to deliver continuous potential business value propositions. The consultant will lead the process to identify and evaluate digital asset capabilities and strengths and develop digital business strategies and roadmap.

• Bachelor’s degree in business, IT or any related field
• 7+ years of experience in global consulting firm with a focus on digital transformation, Data Strategy, performance improvement
• Strong analytical and problem-solving skill with high commitment to quality client service
• Excellent communication and interpersonal skills with the capacity to motivate and lead a team with enthusiasm, drive and effectiveness

Do you believe you have the qualifications we’re looking for? please send us your review and our recruitment team will contact you with the next steps

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A major player in the UAE is looking to set up a brand-new Data Governance function.

• Develop and execute a comprehensive strategy for establishing a data governance function within the organisation.
• Define the data governance vision, mission, and core principles, aligning them with business goals and regulatory requirements.
• Implement a data governance framework that facilitates self-service data access while ensuring data integrity and responsible use.
• Develop and execute a robust communication strategy to educate stakeholders across the organisation on data governance principles and best practices.
• Foster a collaborative data-centric culture where business units understand the value of data governance and actively participate in data stewardship.
• Work with business leaders to identify and prioritise data initiatives that align with strategic objectives.

• Bachelor's degree in business administration, Information Technology, or a related field with minimum 8 years of experience in data governance and strategy.
• Proven track record of successfully establishing and leading data governance programs in large-scale organisations.
• Excellent communication, collaboration, and stakeholder management skills.
• The ability to influence and build consensus across diverse business stakeholders, IT teams, and senior leadership.
• A strategic mindset with a focus on business outcomes and data-driven decision making.

Dubai, United Arab Emirates | Posted on 08/05/2025

Position Title: Head of Data / AI Strategy & Governance Location: Dubai, UAE Job Type: Full-Time

About myZoi myZoi is a Standard Chartered Ventures fintech that ischanging lives for the better, for those who deserve it the most. We arecommitted to promoting global financial inclusion by offering affordable,accessible, and transparent financial services to the underbankedpopulations.

Our vision

To deliver a level playing field for the unbanked andunderbanked in accessing essential financial services through innovative,data-driven solutions that foster financial inclusion in an affordable,convenient, and transparent fashion.

The Role We are seeking atransformative Head of Data & AI Strategy - an enterprise-wide leaderresponsible for defining the strategic data and AI vision for myZoi. This rolewill play a pivotal role Win establishing an AI-enabled data ecosystem,ensuring governance, integrity, and actionable insights are embedded across allfunctions of the business.

You will be entrusted to craft and lead adata-driven culture, accelerate enterprise-wide AI adoption, and ensureresponsible governance by designing scalable data architecture, leading datagovernance initiatives, overseeing ethical and responsible AI integration,driving data literacy, and unlocking data value to power strategicdecision-making, innovation, and regulatory compliance.

KeyResponsibilities

Strategic Leadership & Enterp rise transformation

• Define and implement the overall enterprise data andAI strategy aligned with global growth, innovation, and operational excellencegoals.
  
• Act as a strategic partner to the executive leadershipteam, influencing business decisions and company direction through datainsights.
  
• Lead enterprise data monetization initiatives,developing new revenue streams leveraging AI and data products.
  
• Lead the development of data models,pipelines, and platforms to support analytical, AI, and operational needs.
  
• Drive a data and AI-enabled transformation across allfunctions, fostering a strong data culture and change adoption at all levels ofthe organization.
  
• Ensure data architecture is scalable andsupports cloud-native, real-time, and AI-driven processing.
  
• Establish data quality, lineage, and master datamanagement frameworks to support business information and AI/ML use cases
  
• Build and lead a cross functional high-performing datateam, covering data/AI governance, architecture, andimplementation.
  

DataStrategy & Architecture

• Develop and maintain the enterprise data strategy,shaping and scaling its impact as a core enabler of business innovation andintelligence .
  
• Collaborate with the leadership team to aligndata and AI strategy with organizational priorities.
  
• Lead the development of data models,pipelines, and platforms to support analytical, AI, and operational needs.
  
• Ensure data architecture is scalable andsupports cloud-native, real-time, and AI-driven processing.
  
• Establish data quality, lineage, and master datamanagement frameworks to support business information and AI/ML use cases
  
• Build and lead a cross functional high-performing datateam, covering data/AI governance, architecture, andimplementation.
  

Data Use & AI Enablement

• Work with all functions (like product, innovation,marketing, engineering, operations, etc.)toidentify opportunities for data driven AI/ML applications across theorganization.
  
• Drive integration of machine learning and intelligentautomation to enhance decision-making and customer experiences.
  
• Promote data and AI literacy across theorganization through training, tools, and awareness campaigns.
  
• Monitor emerging AI trends and appropriate tools toensure myZoi remains on the leading edge of innovation.
  

Data& AI Governance

• Develop and implement data governanceframeworks, including data ownership, stewardship, classification, and datalifecycle management.
  
• Work with Innovation, Technology, Risk &Compliance on Data & AI governance, including model transparency, biasmitigation, and ethical use standards.
  
• Define and implement data/AI standards,policies, and framework across the organization.
  
• Ensure high levels of data quality, accuracy, andcompliance with regulatory requirements (e.g., GDPR, BCBS239, AI, and otherlocal regulations).
  

Risk,Security, and Compliance

• Ensure data and AI security, privacy, and riskcontrols are effectively designed and implemented in alignment with risk, legaland regulatory frameworks.
  
• Def ineaccess control and security frameworks for data assets
  
• Engage with senior leadership, regulators, andindustry bodies on data and AI governance matters.
  

Qualifications& Experience

• 15+ years of progressive experience in dataarchitecture, AI/ML, enterprise data strategy and governance, preferably withinfintech, financial services, or highly regulated industries.
  
• Proven record of accomplishment in designing,scaling, and managing enterprise-wide data and AI initiatives in cloud and hybrid environments (preferablyleveraging AWS tech stack).
  
• Strong knowledge of data governance tools, AI modellifecycle, metadata management, MDM, and data quality practices.
  
• Demonstrated ability to work across businessand technology domains, Deep expertise in cloud data platforms (AWSpreferred), data governance tools, ethical AI, and compliance frameworks.
  
• Strong leadership skills with experience managingdiverse, cross-functional teams and drivingcollaboration and results.
  

Skills& Personal Attributes

• Strategic thinker with deep technical expertise indata and AI,
  
• Capable of translating business vision into actionablestrategies.
  
• Inspirational leader who champions innovation,collaboration, and organi z ationaltransformation.
  
• Excellent communicator with stakeholder engagement andchange management skills.
  
• Focused on driving measurable outcomes and creatingstrategic value from data and AI investments.
  
• Strong analytical mindset, attention todetail, and commitment to data integrity and responsible AI use.
  
• Collaborative and proactive problem-solverwith a passion for enabling innovation through data and AI.
  

At myZoi we strive to create a both a productand a team that embraces equality, inclusion, diversity and freedom. We wantpeople who can be themselves and bring their own brand of value to the team.Come and join us!

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.

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.