Urwah Admin

Al Adyat consultancy

Job Overview:The Data Warehouse Expert will lead the data management, integration, governance, and operations workstreams of the Plant Data Management (PDM) project &ndash; a strategic &ldquo;Smart Plant&rdquo; initiative to create a single source of truth for all critical engineering and production data. This senior role requires a seasoned professional with at least 10 years of experience in data management in the oil &amp; gas industry. A strong background in Microsoft data warehousing technologies and an understanding of plant operational processes are essential for successKey Responsibilities:<ul><li>Evaluate the PDM project infrastructure-related components of bidder proposals, ensuring alignment architecture, data standards, &amp; operational requirements.</li><li>Lead the implementation of single source of truth, focusing on MS technologies including Azure, Microsoft 365, MSSQL, &amp; Power Platform in collaboration with implementation partners.</li><li>Collaborate with the solution enterprise architect to make sure the data warehouse design aligns with the overall solution architecture and IT infrastructure.</li><li>Lead the central repository architecture for integrated data from multiple sources (e.g. SAP, real-time systems, spreadsheets) in line with the PDM project requirements</li><li>Define the data models (schemas, tables, cubes) and storage strategy (on-premises MS SQL Server with potential hybrid cloud) to support reporting and analytics.</li><li>Ensure the configuration of ETL/ELT pipelines (using Microsoft SSIS or Azure Data Factory) to extract data from source systems, transform it, and load it into the warehouse.</li><li>Establish a robust data governance framework within the PDM scope, defining data ownership for different data domains (ensuring business stakeholders are identified as data owners), set up data stewardship roles if needed, and enforce policies for data usage, retention, and lifecycle management.</li><li>Enforce compliance with the company&rsquo;s cybersecurity and data privacy policies</li><li>Work to achieve high availability of the data platform. Implement redundancy and failover mechanisms as appropriate (clustering, backups, mirrored databases, etc.). Ensure disaster recovery plans are in place</li><li>Develop and implement data governance policies, standards, and procedures.</li><li>Collaborate with data owners and stewards to define data definitions, classifications, and quality rules.</li><li>Monitor data quality metrics and lead initiatives to resolve data issues.</li><li>Ensure compliance with data privacy regulations (e.g., GDPR, HIPAA) and internal policies.</li><li>&sect; Maintain data catalogs, metadata repositories, and data lineage documentation.</li><li>Support data governance tools and platforms, ensuring proper configuration and usage.</li><li>Conduct training and awareness programs to promote data governance best practices.</li><li>Design and implement frameworks that enable secure, self-service access to data across departments.</li><li>Promote data literacy by developing training materials and conducting workshops on data usage and governance.</li><li>Support the deployment and adoption of data catalog and self-service BI tools.</li><li>Define and manage role-based access controls to balance data accessibility with security.</li><li>Act as a liaison between IT, data teams, and business stakeholders to and ensure relevant data is discoverable and usable.</li><li>Participate in data governance councils and cross-functional working groups, to align data strategy with business goals.</li><li>Provide guidance on data stewardship responsibilities and best practices.</li></ul>Required Qualifications:Educational Background:<ul><li>Bachelor&rsquo;s degree in Information Management, Computer Science, Business, or a related field.</li><li>3+ years of experience in data governance, data management, or a related discipline.</li><li>Strong understanding of data governance frameworks.</li><li>Familiarity with data privacy laws and regulatory requirements.</li><li>Experience with data governance.</li><li>Excellent communication, collaboration, and problem-solving skills.</li><li>Ability to work independently and manage multiple priorities in a fast-paced environment.</li></ul>Expected Experience<ul><li>10+ years of experience in data management roles, including data warehouse development, system integration, and IT project management.</li><li>5+ Experience must be in the oil &amp; gas industry, dealing with industrial or enterprise data.</li></ul>Technical Skills<ul><li>Deep expertise in Microsoft Data Warehouse technologies &ndash; MS SQL Server, SQL Server Integration Services (SSIS) for ETL, SQL Server Analysis Services (SSAS) for OLAP, and SQL querying/tuning</li><li>Strong knowledge of relational and dimensional data modeling. Ability to design normalized schemas for staging and integration, as well as star/snowflake schemas for analytics.</li><li>Experience with handling large datasets (hundreds of gigabytes to terabytes) efficiently (partitioning, indexing strategies, etc.)</li><li>Hands-on experience integrating multiple systems and platforms Microsoft BizTalk, SAP, &amp; SharePoint online.</li><li>Experience implementing data governance policies and using tools for data quality and metadata management</li><li>Proficient in project management practices</li><li>Certified Data Management Professional (CDMP)</li><li>Data Governance and Stewardship Professional (DGSP)</li><li>Certified Information Privacy Professional (CIPP)</li></ul>Soft Skills:<ul><li>Excellent analytical and research skills.</li><li>Strong communication skills to collaborate with cross-functional teams.</li><li>Strong presentation skills</li></ul>Job Type: Full-timePay: From QAR15,000.00 per monthEducation:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>Data Warehouse : 3 years (Required)</li></ul>Language:<ul><li>Arabic (Required)</li><li>English (Required)</li></ul>License/Certification:<ul><li>degree in Information Management, Computer Science (Required)</li></ul>Location:<ul><li>Doha (Required)</li></ul>

Data Warehouse Expert

Job Profile: Cloud Infrastructure ArchitectJob Overview:The Cloud Infrastructure Architect is responsible for designing and overseeing the deployment of scalable, secure, and high-performance infrastructure to support the implementation of Plant Data Model (PDM) system. This role focuses on hybrid architecture with a strong emphasis on Microsoft technologies, including Azure, Microsoft 365, Intune, and Power Platform.The architect will evaluate infrastructure proposals submitted by implementation partners, ensure alignment with enterprise architecture and cybersecurity standards, and supervise the setup and integration of cloud and on-premises components. The role requires deep technical expertise in cloud infrastructure, virtualization, disaster recovery, and enterprise-grade networking, with proven experience in oil and gas environments.Key Responsibilities:<ul><li>Evaluate the PDM project infrastructure-related components of bidder proposals, ensuring alignment with enterprise architecture, cybersecurity standards, and operational requirements.</li><li>Lead the implementation of hybrid cloud infrastructure to support the PDM solution, with a focus on Microsoft technologies including Azure, Microsoft 365, Intune, and Power Platform in collaboration with implementation partners.</li><li>Lead the deployment and configuration of virtual machines, storage systems, networking components, and backup solutions across on-premises and cloud environments.</li><li>Ensure seamless integration of infrastructure with Active Directory, DNS, SCCM, Intune, and other enterprise services.</li><li>Oversee disaster recovery planning and high availability setup for PDM, ensuring compliance with existing DR architecture and recovery objectives.</li><li>Monitor infrastructure performance across distributed sites (e.g., Ras Laffan, Taweelah, Abu Dhabi), optimizing for latency, bandwidth, and system responsiveness.</li><li>Collaborate with system integration experts to ensure infrastructure readiness for middleware, APIs, and real-time data systems.</li><li>Enforce security protocols including encryption, role-based access controls, and secure remote access via ZTNA and MFA.</li><li>Support infrastructure scalability planning, capacity assessments, and hardware provisioning in coordination with approved vendors.</li><li>Maintain detailed documentation of infrastructure architecture, deployment plans, and operational procedures.</li><li>Provide technical oversight during implementation, testing, and go-live phases, ensuring infrastructure stability and compliance.</li></ul>Required Qualifications:Educational Background:<ul><li>A degree in computer science, Computer Engineering, information technology, or a related field</li></ul>Certifications (Preferred)<ul><li>Microsoft Certified: Azure Solutions Architect Expert</li><li>Certified Kubernetes Administrator (CKA)</li><li>TOGAF or similar enterprise architecture framework</li></ul>Expected Experience<ul><li>Minimum: 7&ndash;10 years of experience in IT infrastructure and cloud architecture</li><li>Preferred: Experience leading or supporting cloud/hybrid deployments for industrial platforms (e.g., AVEVA, Hexagon, Siemens, Bentley)</li></ul>Technical Skills<ul><li>Deep expertise in Microsoft Azure services including Virtual Machines, Azure Active Directory, Azure Storage, Azure Networking, and Azure Monitor.</li><li>Experience with Microsoft 365, Intune, and Power Platform for enterprise productivity, device management, and workflow automation.</li><li>Strong understanding of hybrid cloud architecture, including integration between on-premises infrastructure and cloud services.</li><li>Experience with Docker, Kubernetes, and Azure Kubernetes Service (AKS) for deploying and managing containerized applications in hybrid environments</li><li>Advanced knowledge of Azure Virtual Network (VNet) design, ExpressRoute, VPN gateways, DNS, load balancing, and secure network segmentation.</li></ul>Soft Skills:<ul><li>Excellent analytical and research skills.</li><li>Strong communication skills to collaborate with cross-functional teams.</li><li>Strong presentation skills</li></ul>Job Type: Full-timePay: From QAR15,000.00 per monthEducation:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>IT infrastructure and cloud architecture: 3 years (Required)</li></ul>Language:<ul><li>Arabic (Required)</li><li>English (Required)</li></ul>License/Certification:<ul><li>degree in computer science, Computer Engineering (Required)</li></ul>Location:<ul><li>Doha (Required)</li></ul>

Cloud Infrastructure Architect

Job Profile: AI Expert for Plant Data Model (PDM Project)Job SummaryWe are seeking a highly skilled AI Expert to design, build, and operationalize AI/ML solutions that deliver measurable business outcomes. The ideal candidate combines deep machine learning expertise with strong software engineering practices, MLOps proficiency, and stakeholder collaboration. This role will lead end-to-end projects&mdash;from problem framing and data acquisition to model development, deployment, monitoring, and continuous improvement&mdash;while ensuring compliance with security, privacy, and governance policies.Key Responsibilities&middot; Partner with business stakeholders to translate strategic objectives into AI use cases with clear KPIs and ROI.&middot; Own the full ML lifecycle: data sourcing, feature engineering, model selection, training, evaluation, and production deployment.&middot; Implement robust MLOps: CI/CD for ML, model registry, automated testing, reproducible pipelines, and monitoring (drift, performance, fairness).&middot; Design scalable data/feature pipelines using best practices for data quality, lineage, and governance.&middot; Develop models across domains (e.g., predictive analytics, time series, NLP, computer vision, recommender systems).&middot; Optimize models for efficiency and cost across CPU/GPU, leveraging quantization, distillation, or serving optimizations.&middot; Deploy and maintain models on cloud and on-prem platforms; orchestrate with containers and microservices (Docker/Kubernetes).&middot; Establish and enforce responsible AI practices: privacy-preserving methods, bias detection/mitigation, explainability, and secure handling of data.&middot; Produce high-quality documentation: design docs, runbooks, experiment logs, and user guides; present results to technical and non-technical audiences.&middot; Mentor engineers and analysts; contribute to standards, templates, and reusable components within the AI platform.Minimum Qualifications&middot; Bachelor&rsquo;s degree in computer science, Data Science, Engineering, Mathematics, or related field (or equivalent experience).&middot; 5+ years building and deploying ML models in production environments.&middot; Strong programming skills in Python and experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch).&middot; Hands-on experience with data processing frameworks (e.g., Pandas, Spark), SQL/NoSQL databases, and feature stores.&middot; Proficiency in MLOps tooling (e.g., MLflow, DVC, Kubeflow, Airflow) and CI/CD for ML.&middot; Experience deploying to cloud platforms (e.g., Azure Machine Learning, AWS SageMaker, GCP Vertex AI) and container orchestration (Docker/Kubernetes).&middot; Solid understanding of statistics, experiment design (A/B testing), and model validation techniques.&middot; Excellent communication and stakeholder management skills; ability to articulate complex concepts clearly.Preferred Qualifications&middot; Master&rsquo;s or PhD in a quantitative field.&middot; Experience with NLP (transformers, LLMs, RAG) and computer vision (CNNs, detection/segmentation).&middot; Exposure to time-series forecasting, optimization, and reinforcement learning for industrial use cases.&middot; Experience with Azure ecosystem (Azure ML, Databricks, Data Factory, Synapse) and enterprise integration patterns.&middot; Familiarity with privacy-preserving techniques (differential privacy, federated learning) and model interpretability (SHAP, LIME).&middot; Track record of delivering AI solutions in manufacturing, energy, or operations (e.g., predictive maintenance, process optimization).Technical Stack &amp; Tools&middot; Languages: Python (preferred), SQL; familiarity with C++/Java is a plus.&middot; ML/AI: scikit-learn, TensorFlow, PyTorch, XGBoost, Hugging Face; experiment tracking (MLflow).&middot; Data: Pandas, Spark, Delta/Parquet; data versioning (DVC); feature stores.&middot; Pipelines &amp; Orchestration: Airflow, Prefect, Kubeflow; Docker/Kubernetes for serving.&middot; Monitoring &amp; Observability: Prometheus/Grafana; model drift/performance monitoring tools.&middot; DevOps: Git, GitHub/GitLab, CI/CD, testing frameworks (pytest).&middot; Cloud: Azure (preferred), AWS, GCP; serverless and managed ML services.Core Competencies &amp; Soft Skills&middot; Business acumen with the ability to prioritize use cases based on value and feasibility.&middot; Structured problem solving and hypothesis-driven experimentation.&middot; Clear written and verbal communication, storytelling with data, and visualization skills.&middot; Collaboration and mentorship across cross-functional teams (engineering, operations, compliance).&middot; Ownership mindset with a focus on reliability, safety, and continuous improvement.AI Governance, Security &amp; Compliance&middot; Adhere to corporate data governance policies, security standards, and regulatory requirements (e.g., GDPR where applicable).&middot; Implement role-based access controls, encryption, secure secrets management, and audit trails across the ML stack.&middot; Ensure models meet fairness, transparency, and explainability guidelines; conduct regular risk assessments and reviews.Success Criteria &amp; KPIs&middot; Cycle time from ideation to production (weeks).&middot; Model performance against business KPIs (e.g., accuracy, precision/recall, uplift, cost savings).&middot; Operational reliability (SLA adherence, downtime, incident rate).&middot; Adoption and user satisfaction for AI-enabled products and workflows.Compliance metrics (governance checks passed, audits completed).Job Type: Full-timePay: From QAR15,000.00 per monthEducation:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>AI Expert for Plant Data Model (PDM Project) : 3 years (Required)</li></ul>Language:<ul><li>Arabic (Required)</li><li>English (Required)</li></ul>License/Certification:<ul><li>degree in computer science, Data Science (Required)</li></ul>Location:<ul><li>Doha (Required)</li></ul>

AI Expert for Plant Data Model (PDM Project)

Join Al Adyat consultancy and explore 3   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Al Adyat consultancy

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Data Warehouse Expert

Cloud Infrastructure Architect

AI Expert for Plant Data Model (PDM Project)