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

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

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senior data modeler consultant Jobs in Riyadh

senior data modeler consultant

senior data scientist

senior data engineer

SiFi

<div>
 
 
 About Us
 
 
 
 
 We are building the next-generation Office of the CFO that simplifies finance for all businesses.
 
 
 
 SiFi is a corporate expense management platform designed to empower accounting teams with seamless control over corporate spending. Our platform allows companies to issue cards with specific spending restrictions, ensuring funds are used efficiently and only for approved expenses.
 
 
 
 As we scale, trusted data becomes core infrastructure powering financial correctness, operational visibility, and AI-powered automation.
 
 
 
 
 About the Role
 
 
 
 
 We are looking for a Senior Data Engineer to help define and scale the foundation of SiFi&rsquo;s data platform.
 
 
 
 You will be part of the Data &amp; AI team and serve as a key partner to Finance, Product, Engineering, Operations, and Compliance. Your primary responsibility will be to design and own our data platform, modeling standards, and AI-ready infrastructure, ensuring that metrics are accurate, scalable, and trusted across the organization.
 
 
 
 This is a high-ownership role focused on building financial data infrastructure from first principles.
 
 
 
 This role is based in Saudi Arabia (Relocation).
 
 
 
 
 
 
 
 What You Will Own
 
 
 
 
 
 Data Modeling and Standards
 
 
 
 <ul>
 <li>
 Define and maintain scalable data models in SQL
 
 </li>
 <li>
 Establish structured warehouse layers and modeling best practices
 
 </li>
 <li>
 Own KPI definitions and ensure a single source of truth
 
 </li>
 <li>
 Ensure financial correctness and metric consistency
 
 </li>
 </ul>
 
 
 Warehouse Architecture
 
 
 
 <ul>
 <li>
 Design and evolve our cloud data warehouse in BigQuery
 
 </li>
 <li>
 Own transformation workflows using dbt, SQLMesh, or similar tools
 
 </li>
 <li>
 Optimize performance, reliability, and cost
 
 </li>
 <li>
 Design and support production-grade AI/ML pipelines ensuring model performance, data integrity, and compliance.
 
 </li>
 </ul>
 
 
 Reliability and Governance
 
 
 
 <ul>
 <li>
 Ensure data quality, integrity, and observability
 
 </li>
 <li>
 Implement access controls aligned with compliance requirements
 
 </li>
 <li>
 Build a scalable foundation ready for advanced analytics and AI
 
 </li>
 </ul>
 
 
 Cross-Functional Impact
 
 
 
 <ul>
 <li>
 Translate business requirements into robust data systems
 
 </li>
 <li>
 Enable trusted reporting and BI across teams
 
 </li>
 <li>
 Support experimentation and AI-driven initiatives with well-structured datasets
 
 
 
 
 </li>
 </ul>
 Requirements
 
 
 
 What We Are Looking For
 
 
 <ul>
 <li>
 5+ years of experience in Data Engineering or Analytics Engineering
 
 </li>
 <li>
 Strong SQL expertise with hands-on data modeling experience
 
 </li>
 <li>
 Experience with cloud data warehouses such as BigQuery
 
 </li>
 <li>
 Experience with modern transformation frameworks such as dbt or SQLMesh
 
 </li>
 <li>
 Experience building or supporting production-grade AI/ML pipelines is a strong plus
 
 </li>
 <li>
 Ability to operate independently in a fast-moving startup
 
 </li>
 <li>
 Operates with high agency, taking end-to-end ownership of complex problems and delivering outcomes
 </li>
 </ul>
</div>

Senior Data Engineer (Data & AI)

Mirai, a Scopely company

<div>
 Our Generative AI products are only as good as the data behind them. This role owns that data layer from end to end: the pipelines that bring data in, the transformations that shape it, and the way it reaches retrieval systems, agents, and analytics. The work runs on AWS, and the aim is a single governed source that every consumer can rely on.
 
 
 We want someone who has already built data pipelines for AI systems, not only for reporting. Preparing data for an LLM or an agent brings its own work around chunking, embeddings, indexing, and keeping content current, and you have done it before. The team is small and spans several languages, so you will own your pipelines and help set the standards the rest of us follow.
 
 
 
 What You Will Do
 
 
 
 <ul>
 <li>
 Build and run the batch and streaming pipelines that move data from source systems into the lake and through to the warehouse, owning the layers in between from raw to curated, along with their schema, quality, and lineage
 </li>
 <li>
 Build the data layer behind retrieval: source connectors, document parsing, chunking, embedding generation, and vector indexing, including re-embedding when content changes
 </li>
 <li>
 Model curated, query-ready datasets and metrics so AI and analytics consumers work from one definition instead of each rebuilding the logic
 </li>
 <li>
 Add quality checks, validation, and monitoring so problems surface before they reach a model or a user
 </li>
 <li>
 Apply access control where it belongs: row and column level rules, PII handling, and entitlement-aware datasets, enforced as close to query time as the stack allows
 </li>
 <li>
 Work with the platform and DevOps engineers to expose data and retrieval as documented, dependable services
 </li>
 <li>
 Keep storage, compute, and query costs in check, with particular attention to the cost of embedding and vector workloads
 </li>
 <li>
 Review code, write the documentation, and help shape how the team builds its data layer
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Eight or more years in data engineering overall. That includes hands-on work building data for AI or ML systems such as retrieval, embeddings, or feature data, which can be a more recent part of your background
 </li>
 <li>
 Strong SQL and strong Python, including PySpark or similar distributed processing
 </li>
 <li>
 Production experience across the AWS data stack: S3 for the lake, Glue for ETL and the Data Catalog, Athena for serverless query, and Redshift as the warehouse
 </li>
 <li>
 Hands-on experience with a layered data architecture, whether you call it medallion (bronze, silver, gold), a data lake feeding a warehouse, or a lakehouse, including building the transformation stages that move data from raw to curated
 </li>
 <li>
 Experience with an ELT or integration tool such as Airbyte, Fivetran, or Meltano, including building or maintaining connectors
 </li>
 <li>
 Experience with event-driven pipelines using SQS and SNS, and with at least one streaming or change-data-capture technology such as Kinesis, Amazon MSK, or Debezium
 </li>
 <li>
 Hands-on experience with a semantic or metrics layer over the warehouse, such as Cube or the dbt Semantic Layer
 </li>
 <li>
 Hands-on experience with at least one vector store and embedding workflow: pgvector, Amazon OpenSearch, Pinecone, Weaviate, or Milvus
 </li>
 <li>
 Comfort with columnar and open table formats: Parquet together with Apache Iceberg, Delta Lake, or Hudi
 </li>
 <li>
 Working knowledge of an orchestrator such as Amazon MWAA, Step Functions, Dagster, or Prefect, and enough infrastructure as code to work closely with DevOps
 </li>
 </ul>
</div>

Senior Data Engineer

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

Datamatics Global Services Ltd

<div><h1 class="jobSectionHeader">Senior AI Engineer (Arabic Speaker)</h1>
Location: Riyadh, Saudi Arabia 
Experience: 6&ndash;8 Years 
Employment Type: Full-Time / Contract 
Language Requirement: Native or Fluent Arabic Speaker (Mandatory)<h2 class="jobSectionHeader">
About the Role</h2>
We are seeking a highly skilled Senior AI Engineer (Arabic Speaker) to join our growing AI and Data Science team in Riyadh. The ideal candidate will have strong expertise in Artificial Intelligence, Generative AI, Machine Learning Operations (MLOps), and Cloud-based AI Platforms, with proven experience in designing, developing, deploying, and managing enterprise-grade AI solutions.
The successful candidate will play a key role in building scalable AI systems, implementing GenAI applications, operationalizing machine learning models, and collaborating with business stakeholders to deliver innovative AI-driven solutions that create measurable business impact.<h2 class="jobSectionHeader">
Key Responsibilities</h2><h3 class="jobSectionHeader">
AI &amp; Machine Learning Development</h3><ul><li>
Design, develop, train, and deploy machine learning and deep learning models for enterprise use cases.</li><li>
Build and optimize predictive analytics, NLP, recommendation systems, and intelligent automation solutions.</li><li>
Develop AI-powered applications leveraging Large Language Models (LLMs) and Generative AI technologies.</li><li>
Fine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architectures.</li><li>
Evaluate and benchmark AI models to ensure performance, scalability, and reliability.</li></ul><h3 class="jobSectionHeader">
Generative AI Engineering</h3><ul><li>
Design and implement enterprise GenAI solutions using OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, and other LLM platforms.</li><li>
Develop conversational AI solutions, intelligent assistants, and knowledge management systems.</li><li>
Build prompt engineering frameworks and optimize prompts for business use cases.</li><li>
Implement vector databases and semantic search solutions.</li><li>
Develop AI agents and autonomous workflows using modern AI orchestration frameworks.</li></ul><h3 class="jobSectionHeader">
MLOps &amp; AI Operations</h3><ul><li>
Design and implement end-to-end MLOps pipelines for model training, deployment, monitoring, and lifecycle management.</li><li>
Automate model deployment using CI/CD pipelines and infrastructure-as-code practices.</li><li>
Monitor model performance, drift detection, retraining strategies, and operational KPIs.</li><li>
Establish AI governance, model versioning, reproducibility, and compliance standards.</li><li>
Implement scalable AI platforms supporting multiple business units.</li></ul><h3 class="jobSectionHeader">
Cloud &amp; Platform Engineering</h3><ul><li>
Deploy AI/ML workloads on cloud platforms such as Azure, AWS, GCP, or OCI.</li><li>
Manage containerized AI environments using Docker and Kubernetes.</li><li>
Design scalable AI infrastructure supporting high-volume enterprise workloads.</li><li>
Optimize cloud resources, performance, and operational costs.</li></ul><h3 class="jobSectionHeader">
Data Engineering &amp; Integration</h3><ul><li>
Collaborate with data engineering teams to build AI-ready data pipelines.</li><li>
Integrate AI solutions with enterprise applications, APIs, databases, and business platforms.</li><li>
Ensure data quality, security, privacy, and compliance with organizational standards.</li></ul><h3 class="jobSectionHeader">
Stakeholder Management</h3><ul><li>
Engage with business stakeholders to identify AI opportunities and translate business requirements into technical solutions.</li><li>
Present AI solution architectures, recommendations, and project outcomes to technical and non-technical audiences.</li><li>
Mentor junior AI engineers, data scientists, and platform engineers.</li></ul><h2 class="jobSectionHeader">
Required Technical Skills</h2><h3 class="jobSectionHeader">
Artificial Intelligence &amp; Machine Learning</h3><ul><li>
Machine Learning</li><li>
Deep Learning</li><li>
Natural Language Processing (NLP)</li><li>
Predictive Analytics</li><li>
Computer Vision (preferred)</li><li>
Reinforcement Learning (preferred)</li></ul><h3 class="jobSectionHeader">
Generative AI</h3><ul><li>
Large Language Models (LLMs)</li><li>
Retrieval-Augmented Generation (RAG)</li><li>
Prompt Engineering</li><li>
AI Agents &amp; Multi-Agent Systems</li><li>
Fine-Tuning and Model Optimization</li><li>
Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS)</li><li>
LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen</li></ul><h3 class="jobSectionHeader">
MLOps</h3><ul><li>
MLflow</li><li>
Kubeflow</li><li>
Airflow</li><li>
Model Monitoring &amp; Observability</li><li>
CI/CD for ML</li><li>
Feature Stores</li><li>
Model Registry</li><li>
Experiment Tracking</li><li>
Model Governance</li></ul><h3 class="jobSectionHeader">
Cloud Platforms</h3><ul><li>
Microsoft Azure</li><li>
AWS</li><li>
Google Cloud Platform (GCP)</li><li>
Oracle Cloud Infrastructure (OCI) &ndash; Preferred</li></ul><h3 class="jobSectionHeader">
Containers &amp; DevOps</h3><ul><li>
Docker</li><li>
Kubernetes</li><li>
Git</li><li>
GitHub Actions</li><li>
Jenkins</li><li>
Terraform</li><li>
Infrastructure as Code</li></ul><h3 class="jobSectionHeader">
Programming Languages</h3><ul><li>
Python (Mandatory)</li><li>
SQL</li><li>
Bash/Shell Scripting</li><li>
Java or C# (Preferred)</li></ul><h2 class="jobSectionHeader">
Qualifications</h2><ul><li>
Bachelor's Degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.</li><li>
Master's Degree in AI, Machine Learning, Data Science, or related field is highly preferred.</li></ul><h2 class="jobSectionHeader">
Experience Requirements</h2><ul><li>
6&ndash;8 years of experience in AI/ML Engineering, Data Science, or AI Platform Engineering.</li><li>
Minimum 3+ years of hands-on experience implementing Generative AI solutions.</li><li>
Proven experience building and operationalizing machine learning models in production environments.</li><li>
Strong experience implementing enterprise MLOps frameworks and practices.</li><li>
Experience working with cloud-native AI services and modern AI platforms.</li></ul><h2 class="jobSectionHeader">
Preferred Certifications</h2><ul><li>
Microsoft Azure AI Engineer Associate</li><li>
AWS Machine Learning Specialty</li><li>
Google Professional Machine Learning Engineer</li><li>
OCI AI Foundations Associate</li><li>
Kubernetes Certifications (CKA/CKAD)</li><li>
Databricks Machine Learning Professional</li></ul><h2 class="jobSectionHeader">
Soft Skills</h2><ul><li>
Strong analytical and problem-solving skills.</li><li>
Excellent communication and stakeholder management abilities.</li><li>
Ability to work effectively in cross-functional and multicultural environments.</li><li>
Strong ownership, accountability, and leadership mindset.</li><li>
Passion for innovation and continuous learning.</li><li>
Ability to communicate fluently in both Arabic and English.</li></ul><h2 class="jobSectionHeader">
Mandatory Requirements</h2><ul><li>
Native or Fluent Arabic Speaker.</li><li>
6&ndash;8 years of relevant AI/ML engineering experience.</li><li>
Hands-on expertise in Generative AI and MLOps.</li><li>
Strong Python programming skills.</li><li>
Experience deploying AI solutions in enterprise production environments.</li><li>
Willingness to work onsite in Riyadh, Saudi Arabia.</li></ul>
synAh1U1mw</div>

Senior AI Engineer (Arabic Speaker)

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
</div>

Senior Solutions Architect - Data & AI

JAWRAA

<div>
 
 Jawraa is a leading digital transformation partner committed to empowering businesses in Saudi Arabia. With over two decades of experience, we've helped organizations navigate the evolving digital landscape and achieve their goals. Our deep industry expertise and strategic partnerships with top-tier technology providers set us apart.
 
 
 
 
 
 
 About the job :
 
 
 
 We are looking for a Senior Cloud Engineer with deep expertise in Google Cloud Platform (GCP) to join our growing engineering team. In this role, you will be responsible for designing, building, and maintaining scalable, secure, and highly available cloud infrastructure that powers our core products and services. You will partner with software engineers, data teams, and security to lead cloud-native transformation initiatives and champion best practices across the organization.
 
 
 
 
 
 
 Key Responsibilities :
 
 
 
 
 Infrastructure Architecture &amp; Design
 
 
 
 &bull; Architect and implement highly available, fault-tolerant, and scalable cloud solutions on GCP
 
 
 &bull; Lead the design of GCP-native infrastructure using services such as GKE, Cloud Run, Compute Engine, Cloud SQL, BigQuery, Pub/Sub, and Cloud Storage
 
 
 &bull; Define infrastructure standards, patterns, and reference architectures for engineering teams
 
 
 
 
 
 
 DevOps &amp; Automation
 
 
 
 &bull; Build and maintain Infrastructure as Code (IaC) using Terraform and Google Deployment Manager
 
 
 &bull; Design and manage CI/CD pipelines using Cloud Build, GitHub Actions, or similar tooling
 
 
 &bull; Automate cloud operations, monitoring, and remediation using scripting (Python, Bash, Go)
 
 
 
 
 
 
 Security &amp; Compliance
 
 
 
 &bull; Implement and enforce GCP security best practices including IAM, VPC Service Controls, and Cloud Armor
 
 
 &bull; Ensure compliance with regulatory frameworks (SOC 2, ISO 27001, GDPR) within the cloud environment
 
 
 &bull; Conduct regular security assessments and drive vulnerability remediation efforts
 
 
 
 
 
 
 Reliability &amp; Performance
 
 
 
 &bull; Define and maintain SLIs, SLOs, and error budgets for cloud infrastructure services
 
 
 &bull; Lead incident response, root cause analysis, and blameless post-mortems
 
 
 &bull; Optimize cloud resource utilization and drive cost management through FinOps practices
 
 
 
 
 
 
 Collaboration &amp; Leadership
 
 
 
 &bull; Mentor junior and mid-level cloud engineers and promote a culture of learning
 
 
 &bull; Collaborate with product, data, and security teams to align cloud strategy with business goals
 
 
 &bull; Document architecture decisions, runbooks, and operational procedures
 
 
 
 
 
 
 Google Cloud Networking
 
 
 
 &bull; Design and manage Google Cloud VPC networks, subnets, firewall rules, and network policies
 
 
 &bull; Configure and optimize Cloud Load Balancing (HTTP(S), TCP/SSL, Internal) for high-availability workloads
 
 
 &bull; Implement Cloud CDN, Cloud DNS, and Traffic Director for global traffic management
 
 
 &bull; Set up and manage hybrid connectivity using Cloud Interconnect (Dedicated &amp; Partner) and Cloud VPN
 
 
 &bull; Deploy and configure Shared VPC and VPC Network Peering for multi-project architectures
 
 
 &bull; Apply network security controls including Cloud Armor (WAF/DDoS), VPC Service Controls, and Private Google Access
 
 
 &bull; Monitor and troubleshoot network performance using Network Intelligence Center, Connectivity Tests, and VPC Flow Logs
 
 
 &bull; Design private networking for GKE clusters using Alias IP ranges, Cloud NAT, and Private Service Connect
 
 
 
 
 
 
 Requirements :
 
 
 
 &bull; Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field &mdash; or equivalent practical experience.
 
 
 &bull; 7+ years of experience in cloud engineering, with at least 5 years hands-on with GCP
 
 
 &bull; Deep expertise in GCP services: GKE, Cloud Run, BigQuery, Pub/Sub, Cloud Functions, VPC, IAM
 
 
 &bull; Proficiency in Infrastructure as Code using Terraform
 
 
 &bull; Strong programming/scripting skills in Python, Go, or Bash
 
 
 &bull; Experience with Kubernetes and containerized workloads
 
 
 &bull; Hands-on experience with CI/CD tooling and GitOps workflows
 
 
 &bull; Solid understanding of networking concepts: DNS, VPNs, load balancing, CDN, TCP/IP
 
 
 &bull; Experience implementing security controls and compliance in cloud environments
 
 
 &bull; Google Cloud Professional certifications (Cloud Architect, DevOps Engineer, Security Engineer)
 
 
 &bull; Experience with multi-cloud or hybrid cloud architectures
 
 
 &bull; Familiarity with data engineering tools: Dataflow, Dataproc, BigQuery ML
 
 
 &bull; Experience with service mesh technologies (Istio, Anthos Service Mesh)
 
 
 &bull; Background in SRE principles and practices
 
 
 
 
 
 
 
 
 
 Required Specialized Certifications :
 
 
 
 Google Professional Cloud Architect
 
 
 Google Professional DevOps Engineer
 
 
 Google Professional Cloud Security Engineer
 
 
 Google Associate Cloud Engineer
 
</div>

Senior Cloud Engineer {GCP}

Hudson Manpower

<div>We have an urgent opening with one of our prestigious clients in Saudi Arabia for the following position:<h3 class="jobSectionHeader">
Position: Senior Civil / Construction Engineer</h3>
Project:Residential &amp; High-Rise Buildings 
Location: Saudi Arabia
Salary: SAR 10,000 &ndash; 12,000 Basic + Food, Accommodation &amp; Transportation (FAT)<h3 class="jobSectionHeader">
Job Requirements:</h3><ul><li>
Bachelor's Degree in Civil Engineering.</li><li>
Minimum 10+ years of experience in Civil/Construction.</li><li>
Minimum 8&ndash;10 years of experience in Residential and High-Rise Building Projects.</li><li>
At least 3+ years of experience as a Senior Engineer, Lead Engineer, or Project Lead.</li><li>
Strong experience in construction execution, project coordination, and site management.</li></ul><div>
Nationality: As per the client's approved visa allocation and project requirements.</div>
If you are interested in this opportunity, kindly reply with the following details:
We look forward to hearing from you. 
Strong business development experience with ARAMCO and SABIC.</div>

Senior Civil/Construction Engineer | Saudi Arabia

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