[ksa] data & ai – senior consultant / associate manager

business analyst

senior data engineer

[ksa] data & ai – senior consultant / associate manager Jobs in Riyadh

4261- data engineer

ai & advanced analytic specialist Jobs in Riyadh

ai & advanced analytic specialist

data scientist

McKinsey & Company

<div>
 
 Who You'll Work With
 
 
 
 Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.
 
 
 In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues&mdash;at all levels&mdash;will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won&rsquo;t find anywhere else.
 
 
 When you join us, you will have:
 
 
 <ul>
 <li>
 Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
 </li>
 <li>
 A voice that matters: From day one, we value your ideas and contributions. You&rsquo;ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
 </li>
 <li>
 Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm&rsquo;s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you&rsquo;ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
 </li>
 <li>
 World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.
 
 
 </li>
 </ul>
 
 Your Impact
 
 
 
 In the role of a Capabilities &amp; Insights Analytics Analyst, you will be part of our consulting teams with a focus on quantitative analyses and AI/ML approaches, continuously developing our portfolio of data-driven solutions and innovative approaches.
 
 
 You will work closely with our healthcare clients from various sectors such as public bodies, health insurance companies, or providers, utilizing your project management skills and communication with diverse stakeholders.
 
 
 As a Healthcare Analytics Analyst, you are expected to handle large datasets, particularly in analysis and modeling. Your daily tasks will include analyzing and modeling large data sets, as well as working closely with our Data Engineers in building and maintaining our proprietary platforms and solutions. You will develop dashboards and ML/AI models, utilizing both low-code/no-code tools and Python and visualization tools.
 
 
 In daily operations, you will collaborate closely with our Data Engineering colleagues, our Knowledge and Insights experts, and our consulting teams to prepare and execute client work. Besides serving clients as part of an engagement, you will be helping to build healthcare assets and knowledge, driving the firm&rsquo;s proprietary innovation portfolio.
 
 
 We offer challenging tasks in an exceptionally dedicated team with many opportunities for further growth and personal development.
 
 
 
 Your Qualifications and Skills
 
 
 
 <ul>
 <li>
 Successfully completed degree in computer or data analytics/science, ideally combined with biostatistics, bioinformatics or epidemiology
 </li>
 <li>
 3+ years of professional experience in a relevant field (e.g., as a Data Analyst/Scientist, BI, or consulting)
 </li>
 <li>
 Solid understanding and application of Programming in Python and/or R
 </li>
 <li>
 Experience with machine learning frameworks (TensorFlow, PyTorch) and data visualization tools (Tableau, Power BI, Plotly)
 </li>
 <li>
 Familiarity with SQL and data querying from relational databases or cloud-based environments
 </li>
 <li>
 Understanding of electronic health record structures, clinical terminologies (ICD, CPT, SNOMED) and health data standards such as HL7 and FHIR
 </li>
 <li>
 Excellent problem-solving skills, particularly in analytical and quantitative areas
 </li>
 <li>
 Strong entrepreneurial mindset with the motivation to continuously improve the status quo and drive this independently
 </li>
 <li>
 Willingness and ability to travel to client and McKinsey locations within and outside the country
 </li>
 <li>
 Ability to work collaboratively in a team environment and effectively with people at all levels in an organization
 </li>
 <li>
 Excellent written and verbal communication skills in Arabic and English
 </li>
 </ul>
</div>

Capabilities & Insights Analytics Analyst - Healthcare

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

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

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

atmaal

<div>
 
 AI &amp; Advanced Analytics Specialist .
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 
 &bull; Collaborate with business stakeholders to translate strategic objectives into data-driven solutions and advanced analytics use cases.
 
 
 &bull; Design and develop predictive models including forecasting, classification, regression, and customer segmentation.
 
 
 &bull; Apply machine learning and optimization techniques to generate actionable business recommendations.
 
 
 &bull; Utilize Natural Language Processing (NLP) techniques for sentiment analysis, text classification, and information extraction from unstructured data.
 
 
 &bull; Conduct exploratory data analysis to identify trends, anomalies, and opportunities for business improvement.
 
 
 &bull; Leverage Generative AI capabilities for intelligent automation, content summarization, code generation, and insight extraction.
 
 
 &bull; Develop and deploy analytical solutions using modern cloud-based platforms and AI services.
 
 
 &bull; Build interactive dashboards and visualizations that effectively communicate insights to both technical and non-technical stakeholders.
 
 
 &bull; Monitor, validate, and continuously improve analytical models to ensure performance and reliability.
 
 
 &bull; Maintain proper documentation, methodology standards, and reproducible analytics workflows.
 
 
 
 
 
 Requirements:
 
 
 
 
 
 &bull; Bachelor's degree in Data Science, Computer Science, Artificial Intelligence, Statistics, Mathematics, or a related field.
 
 
 &bull; 3&ndash;4 years of experience in Data Science, Advanced Analytics, Machine Learning, or Artificial Intelligence.
 
 
 &bull; Strong proficiency in Python.
 
 
 &bull; Hands-on experience with Power BI.
 
 
 &bull; Experience with Google Cloud Platform (GCP), including BigQuery, Vertex AI, and Google Cloud Storage.
 
 
 &bull; Practical experience in Machine Learning, Predictive Analytics, and NLP.
 
 
 &bull; Exposure to Generative AI technologies and Large Language Models (LLMs) is highly preferred.
 
 
 &bull; Strong analytical, problem-solving, and stakeholder management skills.
 
 
 
 
 
 Preferred Language Level:
 
 
 
 
 
 &bull; Professional working proficiency in English (written and verbal).
 
</div>

AI & Advanced Analytic Specialist

Proven

Key Responsibilities:<ul><li>Design and develop AI/ML models for real-world applications</li><li>Build and deploy scalable machine learning pipelines</li><li>Work with large datasets for training, validation, and optimization</li><li>Develop and integrate NLP, computer vision, or predictive analytics solutions (as required)</li><li>Collaborate with data engineers, software developers, and product teams</li><li>Optimize model performance and ensure production readiness</li><li>Stay updated with latest AI frameworks and technologies</li></ul>Requirements:<ul><li>Minimum 5 years of experience in AI/ML development</li><li>Strong experience with Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn)</li><li>Solid understanding of machine learning, deep learning, and statistical modeling</li><li>Experience with data preprocessing, feature engineering, and model evaluation</li><li>Familiarity with deploying models in cloud environments (AWS / Azure / GCP)</li><li>Strong problem-solving and analytical skills</li></ul>Preferred:<ul><li>Experience with NLP, LLMs, or computer vision</li><li>Knowledge of MLOps tools (Docker, Kubernetes, MLflow)</li><li>Experience working in agile product teams</li></ul>Pay: ﷼13,000.00 - ﷼16,000.00 per monthWork Location: In person

AI Developer

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
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 Commercially aware with a solution-selling mindset
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 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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