data modeler

MASTER-WORKS

<div>Master Works is seeking a detail-oriented and analytical Data Management, Specialist to support and lead activities across multiple data management domains. The successful candidate will be responsible for ensuring the accuracy, integrity, security, and accessibility of organizational data by managing data collection, validation, maintenance, governance, and quality processes. You will work closely with cross-functional teams to develop and implement data management standards, improve data quality, ensure compliance with company policies and regulatory requirements, support reporting and analytics, and drive continuous improvement initiatives that enable informed decision-making and operational excellence. 
Key Responsibilities
<ul><li>Develop and maintain enterprise Data Governance frameworks, including policies, standards, procedures, and controls for Data Quality, Metadata, Master Data, Reference Data, and AI Governance.
</li><li>Manage and monitor Data Quality and Metadata by establishing KPIs, conducting assessments, maintaining the Enterprise Data Catalog and Business Glossary, documenting data lineage, and ensuring compliance with organizational and NDMO requirements.
</li><li>Govern Master and Reference Data by standardizing data definitions, assigning Data Owners and business responsibilities, maintaining reference data, and ensuring data consistency, integrity, and compliance across enterprise systems.
</li><li>Design, develop, and maintain Power BI dashboards, reports, and data visualizations by integrating enterprise data sources to support business intelligence, reporting, and informed decision-making.</li><li>
Develop and implement AI Governance policies, standards, and controls, assess AI-related risks, review AI use cases, and ensure the responsible, ethical, and compliant use of AI solutions.</li><li>
Collaborate with business units, IT, Cybersecurity, Data Owners, and other stakeholders to resolve data governance issues, drive continuous improvement initiatives, and ensure effective implementation of governance practices.</li><li>
Prepare and present governance, compliance, quality, and maturity reports, support NDMO and National Data Index (NDI) compliance initiatives, and promote enterprise-wide awareness of Data Governance and AI Governance best practices</li></ul> 

Requirements 
<ul><li>
Bachelor's degree in Data Science, Computer Science, Information Systems, Information Technology, Software Engineering, Artificial Intelligence or Data Analytics.</li><li>
A Master's degree is considered an advantage.
</li><li>Relevant professional certifications (e.g., CDMP, DGSP, Microsoft Power BI Certification, DAMA-related certifications, or AI Governance/AI Ethics certifications) are highly desirable.</li><li>
5&ndash;7 years of relevant experience in Data Management or Data Governance.</li><li>
Demonstrated experience in implementing NDMO controls or similar enterprise data governance frameworks.</li><li>
Experience with metadata management, data quality, master data management, and business intelligence.</li><li>
Experience working with enterprise Data Governance platforms (e.g., Informatica, Collibra, Alation, or equivalent).</li><li>
Hands-on Power BI experience.</li><li>
Experience with AI Governance is highly desirable.</li><li>
Strong analytical and problem-solving skills.</li><li>
Excellent communication and stakeholder management.</li><li>
Ability to lead cross-functional initiatives.</li><li>
Report writing and presentation skills.</li><li>
Strong coordination and project management capabilities.</li></ul>
Technical Skills<ul><li>
Data Governance</li><li>
Data Quality Management</li><li>
Metadata Management</li><li>
Data Catalog</li><li>
Business Glossary</li><li>
Master Data Management (MDM)</li><li>
Reference Data Management (RDM)</li><li>
Power BI</li><li>
SQL (Preferred)</li><li>
Data Modeling Concepts</li><li>
Data Lineage</li><li>
Data Architecture Fundamentals</li><li>
AI Governance Principles
</li></ul>Job location: Client Site</div>

Data Management, Specialist

Devoteam

<div>
 
 Tech for People Unlocks the Future
 
 
 
 At Devoteam, we believe that technology, combined with strong human values, can actively drive change for the better. Discover how Tech for People is shaping the future, creating a positive impact on individuals and the world around us.
 
 
 With over 25 years of passion for technology and a presence in 18+ countries across EMEA and beyond, we are committed to leveraging innovation, expertise, and human-centric values to make a difference.
 
 
 
 Devoteam Culture &amp; Values:
 
 
 
 True innovation is born from a powerful culture, fused with meaningful values.
 
 
 
 Culture:
 
 
 
 
 Fair and courageous
 
 
 
 Everyone is treated fairly &ndash; this fuels bravery. At Devoteam, we always make fair decisions. We listen and are willing to be challenged, taking courageous decisions as a result. We help our employees to progress at every step and congratulate those who deserve it.
 
 
 
 Ambition and results
 
 
 
 Ambition is nurtured at every step &ndash; this drives results. We are ambitious entrepreneurs with a taste for performance, growth and celebrating success. Commitments are always kept as we seek to achieve profitable growth to create value and employment. We aim to bring as much value as possible to our clients, at every touchpoint.
 
 
 
 Learning and innovating
 
 
 
 Curiosity and learning are at our core &ndash; this stimulates innovation. At Devoteam, we are curious. We learn and embrace innovation constantly to meet challenges and build partnerships of excellence.
 
 
 
 Caring and sharing
 
 
 
 A caring attitude is infused into our culture &ndash; this encourages sharing. We believe in the power of teams, we promote support and collaboration.
 
 
 At Devoteam, we care about our teams and want to work in a positive, productive environment. We support the development of talent and careers,
 
 
 
 Values:
 
 
 
 <ul>
 <li>
 Respect
 </li>
 <li>
 Frankness
 </li>
 <li>
 Passion
 
 
 
 </li>
 </ul>
 
 Job Description
 
 
 
 A Data Engineer is expected to develop, monitor, and optimize data quality rules and processes to ensure reliable and accurate enterprise data.
 
 
 They identify and resolve data anomalies through profiling, cleansing, and validation workflows.
 
 
 The role ensures that business decisions are driven by complete, consistent, and high-integrity data across systems.
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Design, implement, and maintain data quality frameworks, rules, and processes to ensure the accuracy, completeness, and reliability of enterprise data.
 </li>
 <li>
 Collaborate with data governance, MDM, and data integration teams to enforce consistent data quality standards across systems.
 </li>
 <li>
 Conduct data profiling, anomaly detection, and validation to identify quality gaps and root causes.
 </li>
 <li>
 Develop automated data quality checks and workflows for continuous monitoring and remediation.
 </li>
 <li>
 Define and manage key data quality metrics (DQ KPIs) and build dashboards to visualize performance trends.
 </li>
 <li>
 Document data quality rules, issue logs, and remediation actions as part of the data governance framework.
 </li>
 <li>
 Work closely with business data stewards and domain owners to define data quality expectations and acceptance thresholds.
 </li>
 <li>
 Support audits, compliance reviews, and data management maturity assessments by providing DQ evidence and reports.
 </li>
 <li>
 Lead the design and deployment of scalable data quality solutions across multiple data domains and systems.
 </li>
 <li>
 Define enterprise data quality standards, policies, and rule frameworks aligned with governance strategy.
 </li>
 <li>
 Establish data quality scorecards, thresholds, and escalation workflows for high-impact issues.
 </li>
 <li>
 Conduct root cause analysis and lead remediation programs for chronic data issues.
 </li>
 <li>
 Mentor junior engineers and promote data quality best practices across teams.
 </li>
 <li>
 Participate in compliance with the local data management regulations (e.g. NDMO, NDI).
 </li>
 <li>
 Design, build, and maintain scalable, secure, and robust data pipelines for efficient data ingestion and transformation, with a strong focus on building quality checks into the infrastructure itself.
 </li>
 <li>
 Collaborate with cross-functional and leadership teams (Data Scientists, Analysts, and Business Leaders) to translate complex business requirements into technical data quality solutions.
 </li>
 <li>
 Research, evaluate, and recommend new data quality tools, technologies, and practices to enhance the reliability, security, and scalability of the data infrastructure.
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Information Management, or related discipline.
 </li>
 <li>
 5+ years of experience in Data Quality, Data Governance, or Data Engineering roles.
 </li>
 <li>
 Proven hands-on experience with enterprise DQ tools (e.g., Informatica DQ/IDMC, Ataccama, Talend DQ, SAS DQ).
 </li>
 <li>
 Strong expertise in data profiling, rule design, standardization, and exception management.
 </li>
 <li>
 Proficiency in SQL and scripting (Python, Shell, or Scala) for advanced data validation.
 </li>
 <li>
 Deep understanding of data governance frameworks and collaboration with data stewards.
 </li>
 <li>
 Ability to design DQ dashboards, scorecards, and KPIs to monitor performance.
 </li>
 <li>
 Strong communication skills for presenting findings and recommendations to business stakeholders.
 </li>
 <li>
 Experience mentoring junior engineers or managing small DQ workstreams.
 </li>
 <li>
 CDMP Associate Certificate and/or Informatica IDQ Certificate and/or IDMC DQ Certificate
 </li>
 <li>
 Experience defining data quality strategy and embedding DQ into enterprise data platforms (MDM, DWH, Data Lake).
 </li>
 <li>
 Understanding of data lineage, root cause analysis, and impact assessment.
 </li>
 <li>
 Knowledge of metadata management and integration with data catalogs.
 </li>
 <li>
 Familiarity with regulatory and compliance requirements (e.g., NDMO, NDI).
 </li>
 <li>
 Ability to automate DQ workflows through orchestration or CI/CD pipelines.
 
 
 
 </li>
 </ul>
 
 Additional Information
 
 
 
 
 Business Unit: Data &amp; Intelligence
 
 
 
 
 Level: Mid - Senior Level
 
</div>

Data Engineer

Maaden

<div>
 
 Job Purpose
 
 
 
 
 JOB DESCRIPTION
 
 
 
 <ul>
 <li>
 The Lead Specialist, Data Science &amp; Analytics, acts as a technical leader and senior practitioner, driving development, deployment, and scaling of Machine Learning, AI, and advanced analytics solutions across Maaden.
 </li>
 <li>
 The role ensures analytics products are designed, validated, industrialized, governed, and adopted at scale, providing measurable value across mining, processing, operations, and enterprise functions.
 </li>
 <li>
 Lead Specialist, Data Science &amp; Analytics is to analyze data, extract insights, and build predictive models that help organizations make smarter decisions and solve difficult problems. By blending expertise in statistics, computer science, and business strategy, they not only analyze complex datasets but also build predictive models that improve operations and shape long-term decisions. With nearly every industry leaning on data today, the demand for skilled professionals continues to grow
 
 
 </li>
 </ul>
 
 Key Accountabilities
 
 
 
 <ul>
 <li>
 Lead End-to-End Data Science Delivery
 </li>
 <li>
 Developing, implementing and maintaining databases and data collection systems
 </li>
 <li>
 Own the full lifecycle of ML/AI initiatives - from problem framing, data exploration, feature engineering, model development, validation, and MLOps handover.
 </li>
 <li>
 Deliver scalable and production-grade models, ensuring alignment with enterprise data governance and AI standards.
 </li>
 <li>
 Performing statistical analysis to understand and interpret data insights
 </li>
 <li>
 Applying data mining techniques to identify patterns, trends, and relationships in large datasets
 </li>
 <li>
 Building predictive models and machine learning algorithms to forecast future outcomes
 </li>
 <li>
 Creating clear data visualizations and reports to communicate findings to stakeholders
 </li>
 <li>
 Working with cross-functional teams to understand business needs and provide data-driven solutions
 </li>
 <li>
 Design and maintain reliable data pipelines and models in partnership with data engineering to ensure data is accurate, timely, and trustworthy for downstream use
 </li>
 <li>
 Ensuring data security and compliance with relevant regulations
 </li>
 <li>
 Drive experimentation, model versioning, automated retraining, and continuous improvement.
 </li>
 <li>
 Translate Business Needs into AI/Analytics Solutions
 </li>
 <li>
 Establish frameworks and operating models that make data science accessible, scalable, and embedded within business and technical functions
 </li>
 <li>
 Engage BU/domain stakeholders to identify value creation opportunities and convert them into actionable analytics use cases.
 </li>
 <li>
 Build value hypotheses, KPIs, success criteria, and solution roadmaps in collaboration with Data &amp; AI leadership and business teams.
 </li>
 <li>
 Industrialize AI/ML Models (ML Ops &amp; Architecture)
 </li>
 <li>
 Partner with data engineering, data platforms, and cloud/OT architecture teams to embed models into enterprise systems and operational layers.
 </li>
 <li>
 Set standards for production deployment, testing, monitoring, drift handling, and lifecycle governance.
 </li>
 <li>
 Ensure seamless integration of predictive and optimization models into enterprise platforms, control systems, and digital twins
 </li>
 <li>
 Leverage machine learning, optimization, and computer vision as enabling tools for performance, reliability, and sustainability improvements
 </li>
 <li>
 Responsible AI, Quality &amp; Governance
 </li>
 <li>
 Ensure compliance with Maaden&rsquo;s Responsible AI, data quality, and data governance frameworks.
 </li>
 <li>
 Promote reproducibility, documentation, lineage tracking, and auditability across all data science assets.
 </li>
 <li>
 Ensure transparency, explainability, and continuous model governance across production and enterprise environments
 </li>
 <li>
 Stakeholder Management &amp; Value Realization
 </li>
 <li>
 Communicate insights, results, risks, and recommendations to decision-makers using compelling narratives and visualization.
 </li>
 <li>
 Track value realization, adoption metrics, and operational impact to ensure measurable benefit.
 
 
 </li>
 </ul>
 
 Minimum Qualifications
 
 
 
 
 Minimum Qualification, Experience and Core Competencies:
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer science, Data Science, Engineering, Mathematics, Statistics, or related fields.
 
 
 </li>
 </ul>
 
 Minimum Experience
 
 
 
 Good to Have Capabilities
 
 
 <ul>
 <li>
 Minimum Experience:
 </li>
 <li>
 6+ years&rsquo; experience in Data Science / Advanced Analytics with industrial, mining, or heavy-asset environments preferred. Including at least 2 years leading or mentoring analytics professionals
 </li>
 <li>
 Proven ability to translate business problems into analytic approaches: define hypotheses, design analyses, and synthesize results into clear recommendations.
 </li>
 <li>
 Strong proficiency with modern ML frameworks and cloud platforms (TensorFlow, PyTorch, Azure, AWS) &ndash; Microsoft AI Factory
 </li>
 <li>
 Strong technical fluency with modern analytics stacks, data modeling, SQL, and experience partnering effectively with engineering teams.
 </li>
 <li>
 Machine Learning &amp; Advanced Analytics
 </li>
 <ul>
 <li>
 Hands-on experience developing and deploying machine learning models, including time-series forecasting, predictive modeling, and optimization use cases
 </li>
 <li>
 Strong understanding of model performance, validation, stability, and business impact
 </li>
 </ul>
 <li>
 Generative AI &amp; AI Agents
 </li>
 <ul>
 <li>
 Practical experience with Generative AI solutions, including copilots, intelligent automation, and agent-based workflows
 </li>
 <li>
 Ability to embed GenAI capabilities into enterprise processes to improve decision-making and operational efficiency
 
 
 </li>
 </ul>
 </ul>
 Preferred Experience &amp; Platforms
 
 
 <ul>
 <li>
 Data Engineering (IT + OT)
 </li>
 <li>
 Experience designing and maintaining data pipelines across IT and OT environments
 </li>
 <li>
 Exposure to sensor data, streaming / real-time data processing, and industrial data sources
 </li>
 <li>
 Ability to collaborate with data engineering teams to ensure reliable, timely, and trusted data flows
 </li>
 <li>
 MLOps / AgentOps
 </li>
 <li>
 Experience in model deployment and lifecycle management, including:
 </li>
 <ul>
 <li>
 Transition from model development to production and scale
 </li>
 <li>
 Monitoring, retraining, versioning, and drift management
 </li>
 </ul>
 <li>
 Familiarity with automation and operationalization of ML/AI workloads
 </li>
 </ul>
 <ul>
 <li>
 Cloud &amp; Analytics Platforms
 </li>
 <li>
 Experience working with enterprise cloud platforms, preferably:
 </li>
 <ul>
 <li>
 Microsoft Azure Data Platform
 </li>
 <li>
 Databricks AI Platform
 </li>
 <li>
 Microsoft AI Foundry / Microsoft AI Factory
 </li>
 </ul>
 <li>
 Understanding of cloud-native architectures for scalable analytics and AI solutions
 
 </li>
 </ul>
 
 Core Competencies
 
 
 
 <ul>
 <li>
 Model Accuracy &amp; Reliability: Performance, drift stability, and operational uptime.
 </li>
 <li>
 Adoption &amp; Business Impact: Value realized, user adoption, integration success.
 </li>
 <li>
 Delivery Velocity: Timeliness of development cycles and deployment readiness.
 </li>
 <li>
 Compliance &amp; Quality: Alignment with Responsible AI, governance, and documentation standards.
 </li>
 </ul>
</div>

Lead Specialist, Data Science & Analytics II

Cognizant

Role Overview
 As a Senior Data Engineer / Tech Lead, you will design, develop, and optimize scalable, enterprise-grade cloud-native data platforms and pipelines on the Microsoft Azure ecosystem . You will possess deep technical ownership and be responsible for implementing modern data architectures (such as Lakehouse and Medallion architecture) . This role requires close collaboration with architects, business analysts, and downstream data consumers to translate complex business requirements into high-performing and secure data solutions.
 
Key Responsibilities
 1.Data Pipeline Design & Orchestration (ADF)
 <ul>
<li>Design, build, and maintain complex, scalable ETL/ELT pipelines using Azure Data Factory (ADF) to ingest heterogeneous data from diverse sources (APIs, SFTP, Oracle Fusion, SQL Server, Event Hubs, etc.)</li>
<li>Implement parameter-driven dynamic pipelines, custom activities, and robust scheduling triggers</li>
<li>Configure and manage Integration Runtimes (Self-Hosted and Azure IR) for secure and efficient on-premise to cloud data movement</li>
</ul>
2.Advanced Big Data Processing (Azure Databricks)
 <ul>
<li>Develop high-performance batch and real-time streaming data pipelines using Azure Databricks, PySpark, Spark SQL, or Scala</li>
<li>Implement Medallion Architecture (Bronze, Silver, and Gold layers) and maintain modern Lakehouse architectures utilizing Delta Lake</li>
<li>Optimize Spark compute usage through parameter-driven jobs, proper cluster scaling, and Databricks serverless compute configurations</li>
<li>Perform deep performance tuning, query optimization, and memory management of heavy Spark workloads</li>
</ul>
3.Data Warehousing & Modeling
 <ul>
<li>Design and refine data models including dimensional modeling, star schemas, and Slowly Changing Dimensions (SCDs)</li>
<li>Optimize databases by writing complex, performant T-SQL queries, stored procedures, and schemas on Azure SQL Database or Azure Synapse Analytics</li>
</ul>
4.Data Governance, Security & DevOps
 <ul>
<li>Enforce data governance, lineage, and access controls across the platform utilizing Unity Catalog .</li>
<li>Secure data architectures utilizing Azure Key Vault, Managed Identities, Service Principals, and VNET-integrated environments</li>
<li>Implement CI/CD pipelines using Git and Azure DevOps to automate database and pipeline deployments</li>
</ul>
5.Leadership & Collaboration
 <ul>
<li>Provide technical mentorship and guidance to junior developers and QA teams</li>
<li>Enforce engineering discipline through standard code reviews, structured pre/post-deployment validations, and thorough documentation</li>
</ul>
Required Skills & Qualifications
 <ul>
<li>Overall Experience: Minimum of 8+ years of professional experience in Data Engineering or Data Warehousing</li>
<li>Azure Experience: 4+ years of dedicated, hands-on experience designing and operating modern data platforms on Microsoft Azure</li>
<li>Programming Languages: Proficient in Python/PySpark, SQL (advanced query optimization, indexing, stored procedures), and optionally Scala</li>
<li>Core Azure Stack: Extensive knowledge of Azure Data Factory, ADLS Gen2, Azure Databricks (Delta Lake), Azure SQL Database, and Azure Synapse Analytics</li>
<li>Big Data Concepts: Robust understanding of Apache Spark architecture, distributed computing, and the Hadoop ecosystem</li>
<li>Data Integration: Strong background in CDC (Change Data Capture) mechanisms, API integrations, and event-driven data streaming (e.g., Event Hubs/Kafka)</li>
<li>Soft Skills: Excellent analytical capabilities, strong documentation skills, and the ability to articulate technical strategies to non-technical business partners</li>
</ul>
Preferred / "Good-to-Have" Qualifications
 <ul>
<li>Certifications: Microsoft Certified: Azure Data Engineer Associate (DP-203), Azure Solutions Architect Expert, or Databricks Certified Associate/Professional</li>
<li>Cloud Platforms: Exposure to multi-cloud environments (e.g., Google Cloud Platform or AWS)</li>
<li>IaC: Experience using Infrastructure as Code (IaC) tools like Terraform or ARM Templates to deploy Azure resources</li>
</ul>

Architect

MENA Consultant

<div>Location: Riyadh, KSA. 
Working Arrangement: on-site. 
Language Requirements: Fluency in Arabic &amp; English (written and spoken). 
Nationalities: Saudi nationals. 
We are seeking a Saudi National Data Engineer &ndash; Cloudera to support the ongoing operations, monitoring, and maintenance of an existing Cloudera data platform and its associated data pipelines. The role will focus on ensuring platform stability, resolving operational issues, supporting data quality and security, and implementing enhancements to maintain reliable, secure, and efficient data platform operations.<h2 class="jobSectionHeader">
Key Requirements</h2><ul><li>
Saudi National.</li><li>
Proven experience supporting Cloudera Data Platform (CDP).</li></ul><h2 class="jobSectionHeader">
Other Qualifications</h2><ul><li>
Bachelor's degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or a related field.</li><li>
Strong analytical and troubleshooting skills.</li><li>
Excellent documentation and reporting capabilities.</li><li>
Strong communication and stakeholder coordination skills.</li></ul><h2 class="jobSectionHeader">
Key Responsibilities</h2><ul><li>
Monitor and support the day-to-day operations of the Cloudera data platform and associated data pipelines.</li><li>
Track batch and real-time job executions and ensure successful processing.</li><li>
Investigate operational issues, perform root cause analysis, and implement corrective actions.</li><li>
Maintain platform availability and ensure compliance with defined SLAs.</li><li>
Implement minor enhancements, fixes, and operational improvements to existing data pipelines.</li><li>
Monitor data quality and support data validation activities.</li><li>
Manage user access requests and support data security and governance controls.</li><li>
Maintain operational documentation, runbooks, and support procedures.</li><li>
Collaborate with infrastructure, governance, and data engineering teams to ensure reliable platform operations.</li><li>
Contribute to continuous improvement initiatives to enhance platform stability, performance, and operational efficiency.</li></ul></div>

Data Engineer – Cloudera

Emdad By Elm

<div>
 
 
 Job Summary
 
 
 
 
 
 
 Responsible for
 
 integrating data from multiple technology systems,
 
 
 databases
 
 , and
 
 data warehouses
 
 , transforming d
 
 ata into actionable insights, and developing intelligent
 
 dashboards and
 
 analytics solutions that support executive decision-making
 
 . The role focuses on data visualization, automation,
 
 AI adoption
 
 , and continuous enhancement to improve technology performance and operational efficiency.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 <ul>
 <li>
 Integrate and consolidate data from enterprise systems, databases, APIs, and data warehouses to build reliable dashboards and reporting solutions.
 </li>
 <li>
 Design, develop, and continuously enhance dashboards using Microsoft Power BI, Tableau, or similar enterprise platforms.
 </li>
 <li>
 Build and maintain centralized dashboards that consolidate all technology metrics into a single source of truth, enabling detailed monitoring and executive decision-making.
 </li>
 <li>
 Analyze technology data to identify trends, risks, anomalies, and performance improvement opportunities by dashboards.
 </li>
 <li>
 Develop automation workflows to streamline reporting processes, reduce manual effort, and improve operational efficiency.
 </li>
 <li>
 Explore and implement AI-powered capabilities to enhance predictive analytics, intelligent reporting, and automated decision support.
 </li>
 <li>
 Work with technology teams to understand technical data structures and translate requirements into scalable analytics solutions.
 </li>
 <li>
 Support continuous improvement initiatives by identifying opportunities to enhance technology products, requests, and operational performance through data-driven insights.
 </li>
 <li>
 Design intelligent automation workflows that proactively detect issues, trigger alerts, generate AI-driven recommendations, and automatically assign actions to relevant stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 
 
 Education
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Information Systems, Information Technology, or a related field.
 </li>
 </ul>
 
 
 Certifications
 
 
 <ul>
 <li>
 
 Microsoft Power BI/ Tableau Certification
 
 </li>
 <li>
 
 SQL / Database Management Certification
 
 (Preferred)
 </li>
 <li>
 
 Data Analytics Certifications
 
 </li>
 <li>
 
 ITIL v4 Foundation
 
 (Preferred)
 </li>
 <li>
 
 AI / Machine Learning Fundamentals Certification
 
 (Preferred)
 </li>
 <li>
 
 Automation Platform Experience (Microsoft Power Automate, n8n, UiPath)
 
 (Preferred)
 </li>
 </ul>
 
 
 Experience
 
 
 <ul>
 <li>
 
 3&ndash;4 years of experience in Data Intelligence, dashboard development, enterprise data integration, automation workflows, and AI-enabled analytics solutions.
 
 </li>
 </ul>
 
 
 Skills
 
 
 <ul>
 <li>
 Advanced
 
 Microsoft Power BI / Tableau Development
 
 </li>
 <li>
 
 Data Visualization &amp; Dashboard Design
 
 </li>
 <li>
 
 Data Integration &amp; System Connectivity (APIs, Databases, Enterprise Systems)
 
 </li>
 <li>
 
 SQL, Data Modeling &amp; Data Warehouse Understanding
 
 </li>
 <li>
 
 Technical Data Analysis &amp; Executive Reporting
 
 </li>
 <li>
 
 Process Automation &amp; Workflow Optimization (Microsoft Power Automate / n8n / UiPath)
 
 </li>
 <li>
 
 AI Tools Adoption &amp; AI-driven Analytics
 
 </li>
 <li>
 Predictive Analytics &amp; Intelligent Reporting
 </li>
 </ul>
</div>

Technology Data Intelligence Specialist

<div>Master Works is seeking a Data &amp; AI, Head an experienced leader to drive and oversee strategic Data &amp; AI initiatives within government, banking, or enterprise environments. The successful candidate will lead cross-functional teams, manage the delivery of Data &amp; AI programs, and drive digital transformation initiatives aligned with business objectives. The role requires strong leadership, strategic thinking, and expertise in data management, artificial intelligence, and enterprise transformation.
Key Responsibilities:<ul><li>
Lead and manage Data &amp; AI projects and delivery operations.</li><li>
Oversee project planning, execution, governance, risks, timelines, and reporting.</li><li>
Manage multidisciplinary teams including Data Engineers, Data Scientists, Analysts, and Project Managers.</li><li>
Ensure successful delivery of projects within scope, budget, and quality standards.</li><li>
Collaborate with executive stakeholders and business leaders to align delivery with strategic goals.</li><li>
Drive Agile methodologies and modern project delivery practices.</li><li>
Manage vendors, partners, and external stakeholders.</li><li>
Support enterprise digital transformation and data-driven initiatives.</li></ul> 
 
 
Requirements 
<ul><li>
Saudi National.</li><li>
Eligible to work in Saudi Arabia.</li><li>
Bachelor&rsquo;s degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.</li><li>
8+ years of experience in Project Management, Data Delivery, AI Programs, or Digital Transformation.</li><li>
Previous experience within Banking, Government, or Large Enterprise environments is highly preferred.</li><li>
Experience managing ministry or government leaders as stakeholders.</li><li>
Experience with risk and vendor management.</li><li>
Proven knowledge of Agile frameworks and enterprise project delivery.</li><li>
Professional proficiency in Arabic and excellent proficiency in English.</li></ul>
Certifications:<ul><li>
PMP</li><li>
PMI-ACP</li><li>
Scrum Master</li><li>
SAFe Agile</li><li>
ITIL</li></ul>
Job Location: Client Site 
 
 
Benefits</div>

Data & AI Delivery, Head

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