planning manager

business analyst

senior data engineer

demand planner

document controller

data modeler

Devoteam

<div>Company Description 
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:
1. Respect 
2. Frankness 
3. Passion
Knowing that success is the result of collaboration. Alone, we go faster, but together, we go further.
To know more about us, please visit: www.devoteam.com 
 
 
Job Description 
Summary Introduction:
Design, implement, optimize enterprise data architecture and models that represent complex data using relational, dimensional, and NoSQL databases, and ensure data is structured for high performance, clarity, and long-term scalability across both operational and analytical systems. Data Modeler will be the translator between business stakeholders and data engineering teams.
Key Responsibilities:<ul><li>
Assessment - Review current data models to understand the AS-IS environment.</li><li>
Conceptual, Logical, and Physical Modeling - Plan, design and maintain blueprints of the TO-BE data models for OLTP (operational), OLAP (analytical), and Enterprise Data Lakehouse environments and how data will be stored, managed and used.</li><li>
Business Alignment - Understand business processes and translate them into robust data requirements and review current report design documents to understand where data model structures can address business requirements.</li><li>
Multi-Paradigm Modeling - Designing 3NF (Third Normal Form) for transactional databases, Dimensional Models (Kimball/Star Schema) for data warehousing, and Data Vault 2.0 for scalable enterprise data lakes.</li><li>
Data Quality - Transform unstructured data into structured data by fixing errors, eliminate redundancies and unnecessary data to optimize data systems.</li><li>
Performance Optimization - Optimize query performance through smart indexing, partitioning, and materialization strategies.</li><li>
Data Governance - Establish, enforce and implement best practices, data naming standards, data definitions, maintain data maps and relevant diagrams for data systems and metadata management.</li><li>
Data Security - Specify rules and guidelines for ensuring data security and compliance. Define procedures for ensuring data are classified according to their sensitivity.</li><li>
Tooling &amp; Documentation - Maintain data schemas using modern standards modeling tools and ensure documentation is accessible to both technical and non-technical users.</li></ul> 

Qualifications 
<ul><li>
B.Sc. Degree with a minimum of 5+ years of dedicated data modeling experience in enterprise relational databases, columnar databases.</li><li>
SQL Proficiency - Write, read, and optimize complex SQL transactional and analytical queries</li><li>
Modern Data Stack Familiarity - Experience modeling for cloud data warehouses/lakehouses (e.g., SQLSERVER, Hadoop, Snowflake, BigQuery, Databricks), working alongside transformation tools (e.g., dbt), and create ERDs for relational systems and dimensional diagrams.</li><li>
Tooling - Proficiency with ER/Studio, Erwin or similar data modeling software.</li><li>
NoSQL/Unstructured Data - Understanding of when and how to model semi-structured data (JSON, Parquet) and NoSQL databases (MongoDB, Cassandra) alongside relational data.</li><li>
Physical Data Management - Understand current data storage constrains and define TO-BE needs with growth allocation.</li><li>
Data Integration - Familiar with ETL tools to define the rules for data transformations and prepare data for big data analytics.</li><li>
Soft Skills: Communication, presentation skills, Business needs, able to lead or mentor a team.</li></ul>
Certificates: W3school SQL Certification, DAMA-CDMP Certification, Microsoft: Azure Data Engineer Associate. 
Additional Information 
Business Unit: DAIC
Level: Mid-senior level</div>

Senior Data Modeler Consultant

Qiddiya | القدية

<div>
 The senior Expert for Data Modeling will be responsible for the deign and implementation of data models incorporating all information centralized BU the CDU team.
 
 
 This currently includes:
 
 
 <ul>
 <li>
 Cost data from Prism
 </li>
 <li>
 Time data from Primavera P6
 </li>
 <li>
 Risk data from Arm
 </li>
 <li>
 Metadata from Aconex related to documents and report content
 </li>
 <li>
 Various spreadsheets and databases implemented by Qiddiya
 
 
 </li>
 </ul>
 The Data Modeling expert will take the existing model developed in PowerBI and enhance it's capabilities, accessibility and scope of analysis to men the needs of the Qiddiya development division
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Enhance the existing data model strategy that covers all development analysis and reporting requirements
 </li>
 <li>
 Ensure clear requirements are provided to data owners so they understand how their data is tagged so it can be incorporated into models
 </li>
 <li>
 Manage the data modeling team, consisting of AI modeling expert, LLM modeling expert and a database technician and assign them tasks that achieve the desired outcome
 </li>
 <li>
 Advise the Data Modeling and Performance &amp; Analytics Director of best practice and possible enhancement to solutions
 </li>
 <li>
 Work with the Data Office to ensure all data and reports are properly governed
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 Qualifications &amp; Experience
 
 
 
 
 Systems development
 
 
 
 <ul>
 <li>
 Implementation of software solutions into established working environments
 </li>
 <li>
 Experienced with the integration of existing software packages
 </li>
 <li>
 Development of workflow and automated process to enhance data capturing routines
 
 
 </li>
 </ul>
 
 Intra- Organization Stakeholder Experience
 
 
 
 <ul>
 <li>
 Effectively liaise with individuals with a variety of experience and authority levels
 </li>
 <li>
 Understand technical solutions and communicate how they solve problems
 
 
 </li>
 </ul>
 
 Team support and development
 
 
 
 <ul>
 <li>
 Assessment of individual and team performance to optimize efficiency
 </li>
 <li>
 Support to individuals with a variety of technical experience to encourage growth and development
 
 
 </li>
 </ul>
 
 Effective delivery within large organizational structures:
 
 
 
 <ul>
 <li>
 Work within the established organizational structure to effectively deliver defined outcomes
 </li>
 <li>
 Help manage messaging within Qiddiya to ensure Implementation is providing a trusted service
 
 
 </li>
 </ul>
 
 Team collaboration:
 
 
 
 <ul>
 <li>
 Work effectively as a team member, sharing responsibility, providing support, maintaining communication, and updating senior team members on progress
 </li>
 <li>
 Communicate and collaborate with other team members, adjacent teams, and external partners, such as consultants
 
 
 </li>
 </ul>
 
 Degree educated in information services and/or data analytics
 
 
 
 
 Established experience of working as part of an owner's team on solutions for large and complex organizations
 
 
 
 
 Preferred Backgrounds
 
 
 
 <ul>
 <li>
 Excellent communication, presentation, and interpersonal skills
 </li>
 <li>
 Fluency in using Microsoft Office
 </li>
 <li>
 Have high ability to work individually and collaboratively with others
 </li>
 <li>
 Have high ability to work effectively under pressure and meet established goals and objectives within the specified deadline
 </li>
 <li>
 Highly motivated and a strong drive to learn including independent learning
 
 
 </li>
 </ul>
 
 What We Offer
 
 
 
 <ul>
 <li>
 Exposure to all aspects of the development business
 </li>
 <li>
 Opportunity to shape large datasets and implement innovative analytical solutions
 </li>
 <li>
 Opportunity to help develop a team with strong core technical skills
 </li>
 <li>
 Long term appointment
 </li>
 </ul>
</div>

Manager - Data Modeling CDUP2086

<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

sirar by stc

<div>
 
 
 About the Company
 
 
 
 
 
 
 Advanced technology and cybersecurity company (sirar) established by stc, the region&rsquo;s ICT and digital services provider, sirar by stc is a cutting-edge cybersecurity provider that empowers organization to take control of their cyber capabilities and digital environments. As experts in business security and privacy. We offer a comprehensive range of solutions that help you to operate online safely, securely, and efficiently.
 
 
 
 
 
 
 Responsibilities
 
 
 
 
 
 <ul>
 <li>
 Support the execution of the enterprise data management and governance strategy aligned with NDMO
 </li>
 <li>
 Assist in implementing and maintaining data governance frameworks, policies, and operating model
 </li>
 <li>
 Ensure adherence to PDPL and data protection requirements through day-to-day data handling practices
 </li>
 <li>
 Execute and monitor the data quality program, including tracking KPIs and supporting Critical Data Elements (CDEs)
 </li>
 <li>
 Manage and track data sharing requests and documentation, ensuring proper approvals and records
 </li>
 <li>
 Maintain and update metadata and data ownership information across business domains (catalog, glossary, lineage)
 </li>
 <li>
 Support Master Data Management (MDM) activities to improve data consistency and quality
 </li>
 <li>
 Assist in implementing data lifecycle, classification, and retention practices
 </li>
 <li>
 Support the use and maintenance of data governance, catalog, and discovery tools
 </li>
 <li>
 Maintain and update RoPA and privacy documentation, and conduct the requierd PIA / TIA assessments
 </li>
 <li>
 Review data sharing agreements and DPAs in coordination with Legal
 </li>
 <li>
 Support AI data governance practices, ensuring data used in AI is compliant and well-governed
 </li>
 <li>
 Support audit activities and NDMO compliance assessments, including documentation and evidence preparation
 </li>
 <li>
 Collaborate with business, IT, Security, and Risk teams to enforce data governance and compliance practices
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Qualifications
 
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Information Systems, Computer Science, or a related field
 </li>
 <li>
 Preferred: Certifications such as CDMP, CIPP or CIPM
 </li>
 </ul>
 
 
 
 
 
 Required Skills
 
 
 
 
 
 <ul>
 <li>
 Good understanding of data governance frameworks (DAMA-DMBOK)
 </li>
 <li>
 Experience in data quality, metadata management, and data lifecycle practices
 </li>
 <li>
 Understanding of PDPL and data privacy requirements
 </li>
 <li>
 Familiarity with data sharing processes and governance
 </li>
 <li>
 Strong analytical, problem-solving, and coordination skills
 </li>
 <li>
 Experience with data governance tools (e.g., Collibra, Informatica, Purview)
 </li>
 <li>
 Hands-on experience with Power BI or Tableau
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Experience:
 
 
 
 
 
 
 1-3 years in relevant experience.
 
 
 
 
 
 
 Important Notice for Candidates:
 
 
 
 
 
 
 By submitting your application, you confirm that you have read and understood sirar's Candidate Privacy Notice and agree to the processing of your personal data in accordance with it.
 
 
 
 
</div>

Data Management Specialist

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

King Salman International Airport

<div>
 
 
 About the Company
 
 
 
 King Salman International Airport is one of the world's most ambitious airport development projects, designed to redefine the future of aviation and contribute to Saudi Arabia&rsquo;s Vision 2030. The airport aims to become a leading global hub by delivering world-class passenger experiences, operational excellence, and innovation-driven services.
 
 
 
 
 
 
 About the Role
 
 
 
 We are seeking an experienced Manager &ndash; Data Management &amp; Operations to lead and enhance data management practices across the organization. The role is responsible for driving data governance, data quality, metadata management, and data lifecycle initiatives while ensuring compliance with organizational and regulatory requirements. The successful candidate will play a key role in enabling data-driven decision-making and maximizing the value of organizational data assets.
 
 
 
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Lead data quality management initiatives to ensure data accuracy, completeness, consistency, and reliability.
 </li>
 <li>
 Oversee data throughout its lifecycle, including creation, storage, usage, archival, and deletion in accordance with retention policies.
 </li>
 <li>
 Establish and maintain metadata repositories to improve data accessibility and utilization across the organization.
 </li>
 <li>
 Ensure data is captured, managed, and utilized effectively from all relevant sources to support business objectives.
 </li>
 <li>
 Conduct data analysis and generate actionable insights to support data-driven decision-making.
 </li>
 <li>
 Monitor data quality issues, implement corrective actions, and maintain high standards of data integrity.
 </li>
 <li>
 Develop performance reports and dashboards to assess the effectiveness of data management and governance practices.
 </li>
 <li>
 Support the implementation of data governance frameworks, standards, policies, and procedures.
 </li>
 <li>
 Collaborate with stakeholders to promote a data-driven culture and improve organizational effectiveness.
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree or higher in Information Technology, Data Management, Computer Science, Information Systems, or a related field.
 </li>
 <li>
 6&ndash;10 years of relevant experience in Data Management, Data Governance, Data Quality, or related disciplines.
 </li>
 <li>
 Experience leading data management initiatives within large organizations is highly preferred.
 </li>
 </ul>
 
 
 
 
 
 Required Skills
 
 
 <ul>
 <li>
 Strong understanding of Data Governance, Data Quality, Metadata Management, Data Privacy, and Data Lifecycle Management.
 </li>
 <li>
 Experience in data analytics, reporting, and performance measurement.
 </li>
 <li>
 Knowledge of data governance frameworks and regulatory compliance requirements.
 </li>
 <li>
 Excellent stakeholder management and communication skills.
 </li>
 <li>
 Excellent command of the English language (written and verbal).
 </li>
 </ul>
 
 
 
 
 
 Location
 
 
 
 Riyadh, Saudi Arabia (On-site)
 
</div>

Manager - Data Management and Operations

Noventiq GCC

<div>
 
 Job Description
 
 
 
 Noventiq is expanding its team &amp; is on the lookout for goal-oriented, self-driven &amp; motivated individuals, to support the next phase of company&rsquo;s growth strategy.
 
 
 Industry: IT/Cloud Services
 
 
 Location: Riyadh, KSA
 
 
 Job Title &ndash; Senior Solutions Architect
 
 
 
 Role Overview
 
 
 
 We are looking for a
 
 Senior Solutions Architect &ndash; Data &amp; AI
 
 who can independently lead customer engagements, shape complex solutions, and drive strategic conversations across business and technology stakeholders.
 
 
 This role requires a
 
 self-driven, client-facing architect
 
 who is comfortable owning the entire solution lifecycle&mdash;from discovery to proposal&mdash;while specializing in
 
 modern data platforms, analytics, and AI/ML solutions on Azure
 
 .
 
 
 
 Fluency in Arabic is mandatory
 
 , as the role will involve direct engagement with Middle East customers.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Client Engagement &amp; Solution Ownership
 </li>
 <li>
 Act as the primary solutions architect in customer discussions&mdash;owning conversations end-to-end without dependency.
 </li>
 <li>
 Lead CXO-level and technical workshops, translating business challenges into scalable Data &amp; AI solutions.
 </li>
 <li>
 Independently drive solution discovery, architecture definition, and proposal creation.
 </li>
 <li>
 Build trusted advisor relationships with customer stakeholders, especially within Arabic-speaking regions.
 </li>
 <li>
 Data, AI &amp; Application Architecture
 </li>
 <li>
 Design and architect end-to-end enterprise solutions, including:
 </li>
 <ul>
 <li>
 Modern Data Platforms (Data Warehouses, Lakehouse, real-time analytics)
 </li>
 <li>
 AI/ML solutions (predictive analytics, NLP, GenAI, copilots)
 </li>
 <li>
 Application architectures (microservices, APIs, event-driven systems)
 </li>
 </ul>
 <li>
 Integrate data platforms with enterprise applications (CRM, ERP, custom apps).
 </li>
 <li>
 Define data strategies, API strategies, and application integration models.
 </li>
 <li>
 Ensure solutions are scalable, secure, high-performing, and cost-optimize
 </li>
 <li>
 Pre-Sales Leadership
 </li>
 <li>
 Lead the technical component of bids, proposals, and RFP responses.
 </li>
 <li>
 Develop high-quality solution artifacts:
 </li>
 <ul>
 <li>
 Architecture diagrams
 </li>
 <li>
 Cost models &amp; TCO optimization
 </li>
 <li>
 Implementation roadmaps
 </li>
 <li>
 Value propositions aligned to business outcomes
 </li>
 </ul>
 <li>
 Participate in solution demos, PoCs, and design validations.
 </li>
 <li>
 Business &amp; Strategic Alignment
 </li>
 <li>
 Translate customer business goals into measurable data and AI outcomes.
 </li>
 <li>
 Identify opportunities for:
 </li>
 <ul>
 <li>
 Data modernization
 </li>
 <li>
 AI adoption and innovation
 </li>
 <li>
 Upsell/cross-sell within existing accounts
 </li>
 </ul>
 <li>
 Balance technical excellence with commercial viability.
 </li>
 <li>
 Collaboration &amp; Delivery Alignment
 </li>
 <li>
 Work closely with sales, delivery, and engineering teams for seamless transition from presales to execution.
 </li>
 <li>
 Provide architectural oversight during initial delivery phases where needed.
 </li>
 <li>
 Mentor junior architects and engineers on Data &amp; AI, and application architecture
 
 </li>
 </ul>
 
 Required Skills &amp; Expertise
 
 
 
 
 Technical &ndash; Data &amp; AI
 
 
 
 <ul>
 <li>
 Strong expertise in Azure Data &amp; AI ecosystem, including:
 </li>
 <ul>
 <li>
 Azure Data Factory / Synapse / Microsoft Fabric
 </li>
 <li>
 Azure Databricks
 </li>
 <li>
 Azure Machine Learning &amp; AI Services (incl. OpenAI)
 </li>
 </ul>
 <li>
 Deep understanding of:
 </li>
 <ul>
 <li>
 Data architecture patterns (Lakehouse, data mesh, etc.)
 </li>
 <li>
 Data governance, security, and compliance
 </li>
 <li>
 AI/ML lifecycle and MLOps
 </li>
 </ul>
 <li>
 Experience in Azure-native and hybrid architectures.
 
 </li>
 </ul>
 
 Technical &ndash; Application &amp; Integration
 
 
 
 <ul>
 <li>
 Strong experience in application architecture, including:
 </li>
 <ul>
 <li>
 Microservices and distributed systems architecture
 </li>
 <li>
 API design and management (REST, GraphQL, API gateways)
 </li>
 <li>
 Event-driven architectures (Kafka, messaging systems)
 </li>
 </ul>
 <li>
 Experience with application modernization:
 </li>
 <ul>
 <li>
 Monolith to microservices transformation
 </li>
 <li>
 Containerization and orchestration (Docker, Kubernetes)
 </li>
 </ul>
 <li>
 Familiarity with integration patterns:
 </li>
 <ul>
 <li>
 Data + application integration (ETL + APIs)
 </li>
 <li>
 Middleware and enterprise integration platforms
 </li>
 </ul>
 <li>
 Understanding of frontend/backend separation and digital application stacks
 
 </li>
 </ul>
 
 Professional
 
 
 
 <ul>
 <li>
 Proven track record of independently handling pre-sales engagements and closing complex deals.
 </li>
 <li>
 Strong ability to articulate business value, not just technical solutions.
 </li>
 <li>
 Experience working with Middle East clients is highly preferred.
 
 
 </li>
 </ul>
 
 Language
 
 
 
 <ul>
 <li>
 Fluency in Arabic (spoken and written) &ndash; mandatory
 </li>
 <li>
 Strong English communication skills
 
 
 </li>
 </ul>
 
 Experience &amp; Qualifications
 
 
 
 <ul>
 <li>
 8+ years of experience in technology consulting / architecture
 </li>
 <li>
 4+ years in Data &amp; AI solutions architecture
 </li>
 <li>
 Strong pre-sales or consulting background with customer-facing roles
 </li>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, or related field
 
 
 </li>
 </ul>
 
 Certifications (preferred But Not Required)
 
 
 
 <ul>
 <li>
 Microsoft Certified: Azure Solutions Architect Expert
 </li>
 <li>
 Microsoft Certified: Azure Data Engineer Associate
 </li>
 <li>
 Microsoft Certified: Azure AI Engineer Associate
 </li>
 <li>
 Microsoft Certified: Designing Azure Solutions
 
 
 </li>
 </ul>
 
 Key Traits for Success
 
 
 
 <ul>
 <li>
 Self-starter with the ability to operate independently in high-stakes environments
 </li>
 <li>
 Strong storytelling and executive communication skills
 </li>
 <li>
 Commercially aware with a solution-selling mindset
 </li>
 <li>
 Passion for Data, AI, and emerging technologies
 
 
 
 
 </li>
 </ul>
 Location: Riyadh - NQKSA, Riyadh, Riyadh, Saudi Arabia
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Senior Solutions Architect - Data & AI

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