14 Data Management jobs in the United Arab Emirates

Overview

We are looking for a highly analytical and business-minded Business Analyst with 2-3 years of experience, ideally with a background in market research and operational analysis. In this role, you will partner closely with cross-functional teams to turn complex data into actionable business insights that drive decision-making, operational efficiency, and strategic growth.

• Analyze internal and external data to identify trends, assess performance, and support business strategy;
• Conduct in-depth market research and competitive analysis to inform product and growth decisions;
• Translate data insights into clear, actionable recommendations that support execution across product, marketing, and operations;
• Build and maintain dashboards, business reports, and performance metrics to monitor KPIs and key initiatives;
• Collaborate with cross-functional teams to define data requirements and support business planning;
• Participate in forecasting, scenario modeling, and business case development;
• Provide ad hoc insights and data support for strategic and operational projects;

• Bachelor's degree in Business, Economics, Data Science, Statistics, or a related field;
• 2-3 years of experience in data analytics or business analysis, with strong exposure to market research;
• Proficient in SQL and at least one analytical tool (e.g., Python, R, Excel);
• Experienced with BI platforms such as Tableau, Power BI, or Looker;
• Strong business acumen and ability to connect data findings to real-world decisions and outcomes;
• Excellent communication skills with the ability to influence stakeholders across departments;

• Experience in a crypto exchange, fintech, or fast-growing tech company;
• Familiarity with user behavior data, growth metrics, and financial KPIs;
• Understanding of web or mobile analytics platforms (e.g., Google Analytics, Mixpanel);

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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Abu Dhabi, United Arab Emirates | Posted on 06/25/2025

Our client is seeking a motivated Analyst to join the Data & AI team , focused on harnessing data and insights to support informed investment decisions. This role centers around knowledge management, stakeholder engagement, reporting, and change management , with a strong emphasis on optimizing the Client’s Document Management System (DMS) to align with strategic business goals.

The Analyst will collaborate cross-functionally with business stakeholders, data engineers, dashboard developers, and data stewards to ensure business needs are effectively met through Data & AI solutions.

Promote a culture of knowledge sharing and collaboration across investment teams and departments.

Ensure employees are informed and trained on knowledge management tools and practices.

Capture, organize, and distribute relevant knowledge effectively and efficiently.

Foster a continuous learning environment by facilitating feedback loops and sharing best practices.

Establish and maintain a Knowledge Management Community of Practice (CoP) to encourage cross-team collaboration and knowledge exchange.

Act as a liaison between business stakeholders and the Data & AI team to gather and validate requirements.

Support end users in the adoption and usage of Data & AI solutions.

Train and enable super-users to champion knowledge and data practices within their teams.

Coordinate with other departments (e.g., HR for training or Communications for branding) to align broader initiatives.

Adapt DMS and associated tools to reflect changes in business priorities and operating models.

Oversee content management including:

Proper document storage and repository management

Permissions and access control

Metadata tagging and classification

Governance compliance and audit readiness

Update taxonomies, templates, and publishing workflows as required.

Develop and maintain reports on usage, risks, permissions, and effectiveness of Data & AI tools.

Monitor system performance and recommend enhancements based on user feedback and business needs.

Drive adoption of new Data & AI tools through structured change management and training initiatives.

Support implementation of new features and capabilities across systems.

Maintain a network of super-users to support change at scale.

Advocate for DMS best practices and keep users updated on process/system changes.

Bachelor’s degree, preferably in a quantitative or analytical discipline.

Strong ability to translate technical concepts into business-friendly language.

Detail-oriented with a knack for data interpretation and analysis.

Familiarity with Microsoft SharePoint, Teams, and PowerApps is preferred.

Excellent communication and stakeholder management skills.

1–2 years of experience in knowledge management, business analysis, or a related field.

Exposure to business process management or application support is a plus.

If you’re passionate about data-driven decision-making and creating a knowledge-first culture, we encourage you to apply.

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!

Data & AI Strategy role (mid-senior level)

Abu Dhabi, United Arab Emirates | Posted on 10/08/2025

The Data & Artificial Intelligence Strategy professional will lead technology transformation, Data Management, and AI initiatives with hands-on experience and a solid track record in project delivery. The candidate combines strong technical expertise with strategic insight and practical implementation skills, ideally from technology consulting, digital implementation, or operational technology backgrounds.

• AI Implementation : Lead the end-to-end deployment of AI solutions that create measurable business value. This involves collaborating with data scientists, engineers, and business stakeholders to design, develop, and scale AI models and applications that address key organizational challenges. Ensure AI initiatives are aligned with business priorities and monitor their impact through key performance indicators.
• Technology Project Execution : Take ownership of technology projects from initiation to completion, ensuring they are delivered on schedule, within budget, and meet quality standards. This includes detailed project planning, resource allocation, risk management, and continuous communication with stakeholders. Apply best practices in project management to navigate challenges and remove blockers for successful delivery.
• Data & Analytics : Oversee data management and analytics activities to ensure data quality, governance, and accessibility. Guide the development of data pipelines, analytics models, and reporting frameworks to empower data-driven decision-making across the organization. Stay current with industry trends in data technologies and AI to recommend enhancements and innovations.
• Digital Engineering : Provide technical guidance on software development life cycles, architecture design, and integration practices. Work closely with engineering teams to ensure that digital solutions are robust, scalable, and maintainable. Encourage adoption of agile methodologies and continuous improvement in engineering processes.
• Technology Assessment : Conduct regular reviews of technology capabilities, identifying gaps and opportunities for improvement. Evaluate emerging technologies for relevance and potential business impact. Develop recommendations and roadmaps for technology upgrades that support strategic goals.
• Automation Implementation : Drive initiatives that leverage technology and AI to automate repetitive tasks and optimize operational workflows. Collaborate across departments to identify automation opportunities and lead pilot projects to test and refine automation solutions, ensuring efficiency gains and cost reductions.
• Technical Guidance : Act as a bridge between technical teams and business units by translating complex technical concepts into clear, actionable insights. Facilitate understanding and alignment among diverse stakeholders to support effective decision-making and foster innovation.
• Contributing to Strategy : Support senior leadership by assessing current technology and AI strategies, identifying risks and opportunities, and developing actionable plans for execution. Work closely with strategy teams to ensure that technology roadmaps align with the overall business vision and market dynamics.
• Vendor Assessment : Evaluate technology vendors, tools, and service providers to ensure they meet organizational needs in quality, cost, and capability. Lead vendor selection processes, including due diligence, pilot evaluations, and contract negotiations, and manage ongoing vendor relationships.
• Project Oversight : Manage external consultants and technology vendors engaged in projects to ensure delivery meets specifications and timelines. Provide clear direction, monitor progress, and coordinate efforts between internal teams and external partners to maintain project momentum.

• 10 to 15 years of relevant experience
• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or related field; Master’s degree preferred
• Practical expertise in machine learning models, data processing, and AI implementation methods
• Proven experience scaling technology solutions and understanding system architecture
• Strong analytical and problem-solving capabilities
• Ability to align technology initiatives with business objectives
• Excellent communication skills adaptable to various audiences
• Effective stakeholder relationship management
• Commitment to quality, attention to detail, and results orientation

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