11 Data Modeling jobs in the United Arab Emirates

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

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.

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.

Graduate or Post Graduate Degree in Computer Science, Computer Engineering, or any relevant field

We are looking for anEnterprise Data Architect to join our team.

• Architect and deliver enterprise solutions leveraging Azure Cloud services – including Azure Data Lake, Synapse Analytics, Azure ML, Cognitive Services, Logic Apps, Service Bus, and API Management
• Lead enterprise application integration projects – design and implement APIs, microservices, event-driven architectures, and secure messaging patterns for system interoperability
• Define data and AI architectures for advanced analytics, machine learning, and AI model deployment on Azure – ensuring scalability, security, and compliance
• Drive cloud migration of enterprise applications and data platforms – including assessment, re-platforming, and modernization strategies
• Establish integration and data governance frameworks ensuring data security, classification, lineage, and compliance with enterprise policies
• Collaborate with business leaders, IT stakeholders, and developers to align technical solutions with strategic objectives and digital transformation initiatives
• Provide solution leadership and detailed architecture documentation (HLD/LLD), ensuring adherence to best practices and performance benchmarks
• Guide DevOps adoption – enable CI/CD pipelines, Infrastructure as Code (Terraform/Bicep), and automated monitoring frameworks for deployed solutions

• 6 to 8 years of proven experience in solution or enterprise architecture roles
• Strong expertise in Azure Cloud, with working knowledge of AWS and GCP architectures
• Demonstrated experience in enterprise application integration, API lifecycle management, microservices, and event-driven architecture
• Deep understanding of data engineering, analytics, and AI/ML deployment pipelines across multiple clouds
• Hands-on experience with containerization and orchestration (Docker, Kubernetes, AKS, EKS, GKE)
• Familiarity with DevOps/MLOps practices and Infrastructure as Code (Terraform, Bicep, CloudFormation, Deployment Manager)
• Knowledge of cloud security, IAM (Azure AD, AWS IAM, Google IAM), compliance standards (GDPR, SOC2, ISO 27001)
• Strong communication and stakeholder management skills with ability to bridge business and technology

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Beinex pursues a system of hybrid work model.

Employees need to show up at the Office when it is necessary.

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Education

• Master or Bachelor’s degree in computer science, information systems management or related field.
• Solution and Architecture certifications such as TOGAF or other.

• More than 5+ years of experience in information technology, with 2+ years spent in data architecture or technology solutions definitions and implementations.
• Extensive experience in banking and financial services domain

• Expertise in Data Architecture, Data Strategy and Roadmap for large and complex organization and systems and implemented large scale end-to-end Data Management & Analytics solutions
• Experience in transforming traditional Data Warehousing approaches to Big Data based approaches and proven track record of managing risks and data security
• Expertise with DW Dimensional modeling techniques, Star & Snowflake schemas, modeling slowly changing dimensions and role playing dimensions, dimensional hierarchies, and data classification
• Experiences in cloud native principals, designs and deployments.
• Extensive experience working with and enhancing Continuous Integration (CI) and Continuous Development (CD) environments
• Expertise in Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, and Data Archival
• Define workload migration strategies using appropriate tools
• Drive delivery in a matrixed environment working with various internal IT partners
• Demonstrated ability to work in a fast paced and changing environment with short deadlines, interruptions, and multiple tasks/projects occurring simultaneously
• Must be able to work independently and have skills in planning, strategy, estimation, scheduling
• Strong problem solving, influencing, communication, and presentation skills, self-starter
• Experience with data processing frameworks and platforms (Informatica, Hadoop, Presto, Tez, Hive, Spark etc.)
• Hands-on experience with related/complementary open source software platforms and languages (e.g. Java, Linux, Python, GIT, Jenkins)
• Exposure to BI tools and reporting software (e.g. MS PowerBI and Tableau)

The IT company Andersen invites a Data Architect in Abu Dhabi to join its team for working with a company from the UAE.

The customer is a government entity that manages public affairs and oversees various corporate and philanthropic projects. The company is embarking on a transformative digital journey to enhance its operational efficiency and customer experiences.

The project focuses on digital transformation in the UAE to develop and support digital solutions, enhance social services, strengthen public engagement, advance international relations, and optimize administrative processes.

• Designing and evolving data architecture across ingestion, transformation, storage, and consumption layers.
• Defining data modeling strategies (conceptual, logical, physical) for structured and unstructured data.
• Architecting data lakes and lakehouses (Delta Lake, Iceberg, Hudi) with bronze-silver-gold layering.
• Leading implementation of ETL/ELT pipelines using Airflow, dbt, Talend, Informatica.
• Ensuring data governance, lineage, and metadata management using tools like Apache Atlas, DataHub, Collibra.
• Collaborating with AI/ML teams to prepare data for model training, including feature engineering and data tagging.
• Integrating streaming solutions (Kafka, Flink, Spark Streaming) for real-time data processing.
• Implementing security frameworks: RBAC, row-level security, encryption, GDPR/HIPAA compliance.
• Supporting BI and analytics platforms (Tableau, Oracle Analytics) with well-structured data models.
• Guiding CI/CD for data pipelines, containerization (Docker), and orchestration (Kubernetes).
• Documenting architectural decisions, integration diagrams, and security models.

• Experience in data architecture, data engineering, or solution architecture roles for 8+ years.
• Hands-on expertise with Oracle technologies.
• Strong understanding of data governance, security, and compliance.
• Experience with AI/ML data preparation and orchestration pipelines.
• Excellent communication and documentation skills.
• Bachelor's or Master's degree in Computer Science, Data Science, or related field.
• Level of English – from Upper-Intermediate and above.

• Experience with LLM integration and AI orchestration tools (e.g., Alteryx).
• Familiarity with mobile data consumption architecture.
• Certifications in cloud platforms (Azure, AWS, GCP).

• Experience in teamwork with leaders in FinTech, Healthcare, Retail, Telecom, and others. Andersen cooperates with such businesses as Samsung, Siemens, Johnson & Johnson, BNP Paribas, Ryanair, Mercedes, TUI, Verivox, Allianz, T-Systems, etc.
• The opportunity to change the project and/or develop expertise in an interesting business domain.
• Job conditions – you can work both fully remotely and from the office or can choose a hybrid variant.
• Guarantee of professional, financial, and career growth! The company has introduced systems of mentoring and adaptation for each new employee.
• The opportunity to earn up to an additional 1,000 USD per month, depending on the level of expertise, which will be included in the annual bonus, by participating in the company's activities.
• Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated.
• Referral program.
• Private health insurance and compensation for sports activities.

Thinking about your next career move? View Andersen’s vacancies and find yours today

About Us

AceNet Consulting is a fast-growing global business and technology consulting firm specializing in business strategy, digital transformation, technology consulting, product development, start-up advisory and fund-raising services to our global clients across banking & financial services, healthcare, supply chain & logistics, consumer retail, manufacturing, eGovernance and other industry sectors.

We are looking for hungry, highly skilled and motivated individuals to join our dynamic team. If you’re passionate about technology and thrive in a fast-paced environment, we want to hear from you.

We are seeking a highly experienced and strategic Senior Data Architect to lead the design and evolution of our enterprise data ecosystem. This critical role will be responsible for defining the architecture roadmap and making key decisions regarding the modernization of the data landscape, specifically managing the transition from legacy systems to a unified, high-performance platform centered around Data Warehouse, Data Lake, Data Security and Master Data Management (MDM) services. The ideal candidate possesses deep technical expertise, a strategic mindset, and a proven ability to govern complex data environments to enable advanced Enterprise Data Analytics.

• Strategic Architecture & Decision Making, Design & Strategy: Define the conceptual, logical, and physical data architecture blueprint, making critical decisions on technology selection, integration patterns, and data flow to align with business strategy.
• Modernization Roadmapping: Lead the planning and execution of the data migration strategy from existing legacy systems to new, standard enterprise platforms.
• Data Platform Management: Define the target state architecture for core data assets, including the optimal deployment, management, and interaction between the Data Warehouse and the Data Lake.
• Performance & Scalability: Ensure the data architecture is robust, highly available, and scalable to meet current and future demands of high-volume data ingestion and complex analytical queries.
• Data Governance & Master Data Management (MDM), MDM Implementation: Own the Master Data Management strategy and architecture, ensuring the accurate definition, governance, and synchronization of critical enterprise data (Customer, Product, Location, etc.) across all new systems.
• Data Security & Compliance: Architect and enforce security and access control policies (e.g., encryption, masking, role-based access) across all data layers, particularly for sensitive data originating from systems like EMR (HIPAA/PHI) and Cybersecurity.
• Data Quality & Lineage: Establish and enforce enterprise data quality standards, metadata management, and data lineage tracking to ensure data trust and regulatory compliance.
• Enterprise Data Analytics & Business Enablement, Analytics Blueprint: Design the data models (dimensional, normalized, Data Vault) within the Data Warehouse and Data Lake to optimize data access for advanced Enterprise Data Analytics, Business Intelligence (BI), and Machine Learning (ML) use cases.
• Integration: Define robust ETL/ELT strategies and pipelines to efficiently ingest, transform, and load data from diverse operational sources into the analytical platforms.
• Stakeholder Alignment: Collaborate with business leaders, data scientists, and analysts to translate complex business requirements into tangible, high-value data architecture solutions.

• 7+ years of progressive experience in Data Architecture, with at least 3 years in a senior, decision-making capacity for an enterprise-level data platform.
• Experience with Data Governance tools (e.g., Collibra, Informatica Axon) or Data Catalogs.
• Extensive experience with Data Warehouse management and design, including performance tuning and large-scale deployment.
• Mandatory experience designing and managing Data Lake services and architectures (e.g., using major cloud providers like AWS, Azure, OCI or GCP).
• Deep, hands-on expertise in Master Data Management (MDM) principles and technologies, including experience selecting and implementing an MDM solution.
• Proven track record of success in leading large-scale system migration or data integration projects, specifically moving from older, disparate systems to standard ERP/CRM/Clinical systems.
• Expert knowledge of data modeling techniques (Conceptual, Logical, Physical), SQL, NoSQL, and modern data streaming/processing frameworks.
• Strong understanding of security frameworks and regulatory compliance requirements relevant to data (e.g., HIPAA, GDPR, CCPA).
• Excellent communication, negotiation, and presentation skills, with the ability to articulate complex architectural concepts to both technical teams and C-level stakeholders.
• Direct experience integrating data from Oracle Fusion, MS Dynamics, and Clinical systems.
• Experience working in healthcare IT industry.
• Certifications such as TOGAF, CDMP, or specialized cloud data certifications (e.g., AWS Certified Data Analytics, Azure Data Engineer)

• Opportunities to work on transformative projects, cutting-edge technology and innovative solutions with leading global firms across industry sectors.
• Continuous investment in employee growth and professional development with a strong focus on up & re-skilling.
• Competitive compensation & benefits, ESOPs and international assignments.
• Supportive environment with healthy work-life balance and a focus on employee well-being.
• Open culture that values diverse perspectives, encourages transparent communication and rewards contributions.

If you are interested in joining our team and meet the qualifications listed above, please apply and submit your resume highlighting why you are the ideal candidate for this position.

Job Type: Contract
Experience: Minimum 15+ years

Job Summary:

We are seeking a highly experienced Data Platform Architect to design and build scalable, high-performance data platforms. The ideal candidate should have a strong background in AWS and other Public cloud services, data engineering, AI platform development, data integrity, and schema design. The role demands expertise in ETL techniques, open-source tools, data migration, and enterprise data architecture.

Key Responsibilities:

• Architect and Design scalable and secure data platforms, ensuring high availability and performance.
• Develop and Optimize data pipelines and ETL processes using modern frameworks and methodologies.
• Implement AI & ML Platforms , ensuring seamless integration with enterprise data ecosystems.
• Ensure Data Integrity & Governance by enforcing best practices for security, compliance, and quality.
• Oversee Data Migration strategies and execution from legacy to modern cloud-based architectures.
• Leverage AWS Services , including but not limited to S3, Redshift, Glue, EMR, Athena, Lambda, DynamoDB, and Kinesis.
• Lead Open Source Adoption , integrating tools like Apache Spark, Airflow, Kafka, and Flink for data processing.
• Collaborate with Cross-Functional Teams including Data Engineers, Data Scientists, and DevOps to streamline data workflows.
• Monitor Performance & Scalability , proactively addressing bottlenecks in data processing and analytics.
• Establish Best Practices for data modeling, schema design, and data architecture across various domains.
• Mentor and Guide engineering teams to enhance data capabilities within the organization.

Required Skills & Qualifications:

• 15+ years of experience in data engineering, data architecture, and cloud-based platforms.
• Expertise in AWS Cloud Services and hands-on experience with data storage, compute, and analytics tools.
• Strong ETL and Data Processing Knowledge , including batch and real-time data streaming.

Tools: Apache NiFi, Talend, Informatica PowerCenter, AWS Glue, Microsoft SSIS, Matillion, Fivetran, Stitch, dbt (data build tool)

• Proficiency in Open-Source Tools like Apache Spark, Hadoop, Airflow, Kafka, Flink, and Presto.
• Deep Understanding of AI & ML Workflows and their integration with data platforms.
• Proven Experience in Data Migration Strategies from on-premises to cloud.
• Expertise in Data Schema Design, Modeling, and Optimization for relational and NoSQL databases.
• Solid Programming Skills in Python, SQL, and Spark.
• Strong Problem-Solving Abilities with an analytical and strategic mindset.
• Excellent Leadership and Communication Skills , capable of working with technical and business stakeholders.

Preferred Qualifications:

• AWS Certified Solutions Architect or AWS Certified Data Analytics Certification.
• Experience working in AI-driven data platforms or MLOps environments .
• Familiarity with Kubernetes, Docker , and CI/CD pipelines for data workflows.

Why Join Us?

• Work with cutting-edge technologies in data and AI.
• Influence key architectural decisions and drive innovation.
• Competitive compensation and benefits package.
• A collaborative and high-performing team environment.

If you are passionate about data platforms and have a strong technical foundation, we invite you to apply and be part of our growing team!