Qureos Mentor

Datamatics Global Services Ltd

<div><h2 class="jobSectionHeader"><b>IBM Cloud Pak Consultant &ndash; Integration</b><br>
<b>Role Type: Full Time</b><br>
<b>Location : KSA - Riyadh</b></h2><h3 class="jobSectionHeader"><b>
Role Summary</b></h3><p>
We are seeking an experienced <b>IBM Cloud Pak Consultant with a strong focus on Integration</b> to design, implement, and support enterprise integration solutions using IBM Cloud Pak for Integration (CP4I). The ideal candidate will have hands-on expertise in API management, messaging, event streaming, and hybrid cloud integration architectures.</p><p></p><h2 class="jobSectionHeader"><b>
Key Responsibilities</b></h2><ul><li>
Design and implement end-to-end integration solutions using <b>IBM Cloud Pak for Integration</b></li><li>
Develop and manage <b>API lifecycle using IBM API Connect</b></li><li>
Build and maintain messaging and event-driven architectures using <b>IBM MQ, Event Streams (Kafka-based)</b></li><li>
Implement integration flows using <b>App Connect Enterprise (ACE)</b></li><li>
Work on containerized deployments using <b>OpenShift / Kubernetes</b></li><li>
Collaborate with enterprise architects to define integration patterns and standards</li><li>
Ensure secure, scalable, and high-performance integration between on-prem and cloud systems</li><li>
Troubleshoot and resolve integration issues across distributed systems</li><li>
Support CI/CD pipelines for integration deployments</li><li>
Provide technical guidance and mentoring to junior developers</li></ul><p></p><h2 class="jobSectionHeader"><b>
Required Skills &amp; Experience</b></h2><ul><li>
5&ndash;10 years of experience in enterprise integration or middleware technologies</li><li>
Strong hands-on experience with <b>IBM Cloud Pak for Integration (CP4I)</b></li><li>
Expertise in:<ul><li>
IBM API Connect</li><li>
IBM App Connect Enterprise (ACE)</li><li>
IBM MQ</li><li>
IBM Event Streams (Kafka)</li></ul></li><li>
Good understanding of <b>microservices architecture</b></li><li>
Experience with <b>Red Hat OpenShift / Kubernetes</b></li><li>
Knowledge of REST/SOAP APIs, JSON, XML</li><li>
Familiarity with DevOps tools (Jenkins, Git, CI/CD pipelines)</li><li>
Strong debugging and performance tuning skills in integration environments</li></ul><p></p><h2 class="jobSectionHeader"><b>
Preferred Qualifications</b></h2><ul><li>
IBM certification in Cloud Pak for Integration or related technologies</li><li>
Experience in hybrid cloud or multi-cloud integration projects</li><li>
Knowledge of security standards (OAuth2, TLS, SSO)</li><li>
Exposure to enterprise industries such as banking, telecom, or insurance</li></ul><p></p><h2 class="jobSectionHeader"><b>
Soft Skills</b></h2><ul><li>
Strong problem-solving and analytical skills</li><li>
Good communication and stakeholder management</li><li>
Ability to work in Agile / Scrum environments</li><li>
Team leadership and mentoring capability</li></ul><p>
</p><p>mKVPuRROEf</p></div>

IBM Cloud Pak Consultant – Integration

<div><h1 class="jobSectionHeader"><b>Linux, Kubernetes &amp; Veeam Infrastructure Engineer</b></h1><p><b>
Location:</b> Riyadh, Saudi Arabia<br>
<b>Employment Type:</b> Full-Time / Contract<br>
<b>Experience Required:</b> 3&ndash;5 Years<br>
<b>Domain:</b> Infrastructure Operations / Platform Engineering / Cybersecurity<br>
<b>Note : Must be Saudi National</b></p><h2 class="jobSectionHeader"><b>
Job Summary</b></h2><p>
We are seeking a highly motivated and technically skilled <b>Linux, Kubernetes &amp; Veeam Infrastructure Engineer</b> to support the administration, security, monitoring, and operational management of enterprise Linux systems, Kubernetes container platforms, and Veeam Backup &amp; Recovery environments.</p><p>
The successful candidate will be responsible for maintaining platform stability, security compliance, backup integrity, disaster recovery readiness, and operational excellence across critical infrastructure environments. This role requires strong expertise in Linux administration, container orchestration, backup and recovery technologies, security hardening, and operational support.</p><h2 class="jobSectionHeader"><b>
Key Responsibilities</b></h2><h3 class="jobSectionHeader"><b>
Linux Systems Administration &amp; Security</b></h3><ul><li>
Administer, maintain, and support Linux-based servers and enterprise services.</li><li>
Perform Linux security hardening in accordance with organizational and industry security standards.</li><li>
Monitor system performance, availability, resource utilization, and service health.</li><li>
Review system logs, user activities, and security events to identify risks and operational issues.</li><li>
Manage operating system patching, upgrades, and vulnerability remediation activities.</li><li>
Conduct configuration compliance assessments and implement corrective actions.</li><li>
Troubleshoot operating system, application, and infrastructure-related issues.</li><li>
Support capacity planning, performance tuning, and operational optimization initiatives.</li></ul><h3 class="jobSectionHeader"><b>
Kubernetes &amp; Container Platform Administration</b></h3><ul><li>
Administer and support Kubernetes clusters and containerized workloads in production environments.</li><li>
Monitor cluster health, node performance, container activities, and orchestration events.</li><li>
Implement and maintain Kubernetes security best practices and governance standards.</li><li>
Validate container image security and perform vulnerability assessments.</li><li>
Configure and monitor container runtime security controls.</li><li>
Manage role-based access control (RBAC), namespaces, policies, and cluster configurations.</li><li>
Support deployment automation and integration with CI/CD pipelines.</li><li>
Integrate Kubernetes platforms with centralized logging, monitoring, SIEM, and cloud security solutions.</li><li>
Perform compliance assessments and remediation activities for containerized environments.</li></ul><h3 class="jobSectionHeader"><b>
Veeam Backup &amp; Recovery Administration</b></h3><ul><li>
Administer and maintain Veeam Backup &amp; Replication infrastructure.</li><li>
Configure, schedule, and monitor backup, replication, and recovery jobs.</li><li>
Perform backup health checks and proactively resolve backup failures.</li><li>
Monitor storage capacity, backup performance, and infrastructure utilization.</li><li>
Conduct regular restore testing to validate backup integrity and recovery readiness.</li><li>
Ensure compliance with backup retention, recovery objectives (RPO/RTO), and organizational policies.</li><li>
Support disaster recovery planning, testing, and documentation.</li><li>
Continuously improve backup and recovery processes and operational procedures.</li></ul><h3 class="jobSectionHeader"><b>
Security &amp; Compliance</b></h3><ul><li>
Support vulnerability management and remediation activities across Linux and Kubernetes environments.</li><li>
Monitor and respond to infrastructure security alerts and incidents.</li><li>
Ensure compliance with security baselines, hardening standards, and operational controls.</li><li>
Assist with audit activities, compliance reporting, and security assessments.</li><li>
Maintain technical documentation, operational procedures, and infrastructure diagrams.</li></ul><h2 class="jobSectionHeader"><b>
Required Technical Skills</b></h2><h3 class="jobSectionHeader"><b>
Linux Administration</b></h3><ul><li>
Red Hat Enterprise Linux (RHEL)</li><li>
Oracle Linux</li><li>
Ubuntu Linux</li><li>
Linux Security Hardening</li><li>
Shell Scripting (Bash)</li><li>
User &amp; Access Management</li><li>
System Performance Monitoring</li><li>
Patch Management</li><li>
Log Analysis &amp; Troubleshooting</li></ul><h3 class="jobSectionHeader"><b>
Kubernetes &amp; Containers</b></h3><ul><li>
Kubernetes Administration</li><li>
Container Security</li><li>
Docker</li><li>
RBAC Management</li><li>
Container Image Security</li><li>
Cluster Monitoring &amp; Troubleshooting</li><li>
Helm</li><li>
Kubernetes Networking</li><li>
Namespace &amp; Policy Management</li></ul><h3 class="jobSectionHeader"><b>
Backup &amp; Recovery</b></h3><ul><li>
Veeam Backup &amp; Replication</li><li>
Backup Administration</li><li>
Replication &amp; Recovery Operations</li><li>
Restore Testing</li><li>
Disaster Recovery Planning</li><li>
Backup Monitoring &amp; Optimization</li></ul><h3 class="jobSectionHeader"><b>
Security &amp; Monitoring</b></h3><ul><li>
Vulnerability Management</li><li>
Configuration Compliance</li><li>
Security Hardening</li><li>
SIEM Integration</li><li>
Centralized Logging</li><li>
Security Monitoring &amp; Incident Response</li></ul><h3 class="jobSectionHeader"><b>
DevOps &amp; Automation (Preferred)</b></h3><ul><li>
CI/CD Pipelines</li><li>
Git</li><li>
Jenkins</li><li>
GitLab CI/CD</li><li>
Ansible</li><li>
Terraform</li><li>
Python (Basic to Intermediate)</li></ul><h2 class="jobSectionHeader"><b>
Qualifications</b></h2><ul><li>
Bachelor&rsquo;s Degree in Computer Science, Information Technology, Engineering, Cybersecurity, or a related field.</li><li>
Relevant certifications are highly desirable.</li></ul><h2 class="jobSectionHeader"><b>
Experience Requirements</b></h2><ul><li>
3&ndash;5 years of hands-on experience in Linux Systems Administration.</li><li>
Experience managing Kubernetes and containerized environments in production.</li><li>
Hands-on experience with Veeam Backup &amp; Replication administration.</li><li>
Experience supporting enterprise infrastructure operations and security compliance initiatives.</li><li>
Experience with vulnerability remediation and operational monitoring.</li></ul><h2 class="jobSectionHeader"><b>
Preferred Certifications</b></h2><h3 class="jobSectionHeader"><b>
Linux</b></h3><ul><li>
RHCSA (Red Hat Certified System Administrator)</li><li>
RHCE (Red Hat Certified Engineer)</li><li>
Linux Professional Institute Certification (LPIC)</li></ul><h3 class="jobSectionHeader"><b>
Kubernetes</b></h3><ul><li>
Certified Kubernetes Administrator (CKA)</li><li>
Certified Kubernetes Security Specialist (CKS)</li><li>
Certified Kubernetes Application Developer (CKAD)</li></ul><h3 class="jobSectionHeader"><b>
Backup &amp; Recovery</b></h3><ul><li>
Veeam Certified Engineer (VMCE)</li></ul><h3 class="jobSectionHeader"><b>
Security</b></h3><ul><li>
Security+</li><li>
CISSP (Preferred)</li><li>
Certified Cloud Security Professional (CCSP)</li></ul><h2 class="jobSectionHeader"><b>
Soft Skills</b></h2><ul><li>
Strong analytical and troubleshooting abilities.</li><li>
Excellent problem-solving skills.</li><li>
Good communication and technical documentation capabilities.</li><li>
Ability to work independently and within cross-functional teams.</li><li>
Strong attention to detail and operational discipline.</li><li>
Ability to manage multiple priorities in a dynamic environment.</li></ul><h2 class="jobSectionHeader"><b>
Must-Have Requirements</b></h2><ul><li>
3&ndash;5 years of Linux Administration experience.</li><li>
Hands-on Kubernetes administration and container security experience.</li><li>
Experience with Veeam Backup &amp; Replication.</li><li>
Linux security hardening and patch management.</li><li>
Backup monitoring, restore testing, and disaster recovery support.</li><li>
Vulnerability remediation and compliance validation experience.</li><li>
Experience supporting production infrastructure environments.</li></ul><p>
</p><p>zl0vKF4keb</p></div>

Linux, Kubernetes & Veeam Infrastructure Engineer (Saudi National)

<div><h1 class="jobSectionHeader"><b>ServiceNow GRC &amp; SecOps Implementation Consultant (Contract &ndash; 6 Months)</b></h1><p><b>
Location:</b> Riyadh, Kingdom of Saudi Arabia<br>
<b>Contract Duration:</b> 6 Months<br>
<b>Employment Type:</b> Contract<br>
<b>Experience </b>: 5 to 7 Years</p><h2 class="jobSectionHeader"><b>
About the Role</b></h2><p>
We are seeking experienced <b>ServiceNow GRC &amp; SecOps Consultants/Developers</b> to support a large-scale ServiceNow implementation program for a leading organization in Saudi Arabia. The selected candidates will play a key role in the design, configuration, customization, integration, and deployment of ServiceNow Integrated Risk Management (IRM), Security Operations (SecOps), Business Continuity Management (BCM), and Third-Party Risk Management (TPRM) modules.</p><p>
This role requires hands-on implementation experience in ServiceNow GRC and Security Operations environments, with exposure to regulatory frameworks applicable to the banking and financial services sector.</p><h2 class="jobSectionHeader"><b>
Key Responsibilities</b></h2><ul><li>
Design, configure, and implement ServiceNow IRM, BCM, TPRM, and SecOps solutions.</li><li>
Gather business and regulatory requirements and translate them into ServiceNow configurations and workflows.</li><li>
Configure and customize:<ul><li>
Policy and Compliance Management</li><li>
Risk Management and Risk Assessments</li><li>
Third-Party Risk Management (TPRM)</li><li>
Business Continuity Management (BCM)</li><li>
Security Incident Response (SIR)</li><li>
Vulnerability Response (VR)</li><li>
Threat Intelligence (TI)</li></ul></li><li>
Develop and maintain ServiceNow workflows, business rules, UI policies, client scripts, and integrations.</li><li>
Configure role-based access controls (RBAC) and security models.</li><li>
Support integration activities with security and monitoring platforms.</li><li>
Participate in testing, defect resolution, deployment, and post-go-live support.</li><li>
Collaborate with stakeholders, project managers, architects, and compliance teams to ensure successful delivery.</li><li>
Ensure platform configurations align with regulatory and governance requirements.</li><li>
Produce technical documentation, solution designs, and implementation guides.</li></ul><h2 class="jobSectionHeader"><b>
Mandatory Technical Skills</b></h2><ul><li>
Strong hands-on experience with <b>ServiceNow Integrated Risk Management (IRM)</b>:<ul><li>
Policy Management</li><li>
Compliance Management</li><li>
Risk Assessments</li><li>
Third-Party Risk Management (TPRM)</li></ul></li><li>
Strong experience with <b>ServiceNow Security Operations (SecOps)</b>:<ul><li>
Security Incident Response (SIR)</li><li>
Vulnerability Response (VR)</li><li>
Threat Intelligence (TI)</li></ul></li><li>
Experience implementing <b>ServiceNow Business Continuity Management (BCM)</b>:<ul><li>
Business Impact Analysis (BIA)</li><li>
BCM Workflows</li><li>
Crisis Management</li></ul></li><li>
Experience with <b>ServiceNow Third-Party Risk Management (TPRM)</b>:<ul><li>
Vendor Lifecycle Management</li><li>
Due Diligence Processes</li><li>
Vendor Tiering Models</li></ul></li><li>
Strong knowledge of ServiceNow platform administration and development:<ul><li>
Update Sets</li><li>
Scripting (JavaScript)</li><li>
Integrations</li><li>
Role-Based Access Controls (RBAC)</li><li>
Workflow Configuration</li></ul></li></ul><h2 class="jobSectionHeader"><b>
Required Experience</b></h2><ul><li>
Minimum <b>3+ years of ServiceNow GRC implementation experience</b>.</li><li>
Overall experience of <b>5+ years in ServiceNow development and implementation projects</b>.</li><li>
Proven experience delivering ServiceNow GRC, BCM, TPRM, and SecOps implementations.</li><li>
Experience working in complex enterprise environments.</li><li>
Ability to work independently and engage directly with business and technical stakeholders.</li></ul><h2 class="jobSectionHeader"><b>
Preferred Qualifications</b></h2><ul><li>
ServiceNow Certified Implementation Specialist (CIS) &ndash; GRC.</li><li>
ServiceNow Certified Implementation Specialist (CIS) &ndash; SecOps.</li><li>
ServiceNow Certified System Administrator (CSA).</li><li>
Additional ServiceNow certifications will be considered an advantage.</li></ul><h2 class="jobSectionHeader"><b>
Desirable Skills</b></h2><ul><li>
Integration experience with:<ul><li>
Qualys</li><li>
Splunk</li><li>
IBM QRadar</li></ul></li><li>
Experience working within regulated financial institutions, including:<ul><li>
Banking</li><li>
Digital Banking</li><li>
FinTech</li></ul></li><li>
Familiarity with regulatory and compliance frameworks:<ul><li>
SAMA Cyber Security Framework (CSF)</li><li>
SAMA IT Governance Framework (ITGF)</li><li>
SAMA Cloud Framework Framework (CFF)</li><li>
NCA Essential Cybersecurity Controls (ECC)</li><li>
PCI-DSS</li><li>
ISO 22301</li></ul></li><li>
Arabic language proficiency is desirable but not mandatory.</li></ul><p>
</p><p>2sHL0vbrjx</p></div>

ServiceNow GRC & SecOps Implementation Consultant

<div><b>Job Description &ndash; 1 x Data Modeller (Erwin Data Modeler)</b><br>
<b>Location: Abudhabi - UAE - Onsite</b><br>
<b>Open to Relocate</b><br>
<b>Duration: 6 months ( Extendable to One Year)</b><br>
<b>Experience: 5 to 7 Years</b><br>
<b>Project start date is 1st July - Immediate joiners will be preferred</b><br>
<br>
<b>Role Overview</b><br>
The Data Modeller will be responsible for establishing and managing the enterprise data modelling capability for ADC using Erwin Data Modeler. The role will lead the design and delivery of authoritative data register models across conceptual, logical, and physical layers while ensuring alignment with government data standards, enterprise architecture requirements, and target platform implementations.<br>
<br>
<b>Key Responsibilities</b><br>
<b>Erwin Environment Setup and Governance</b><ul><li>
Configure and administer the Erwin Data Modeler environment for ADC.</li><li>
Establish and maintain the Erwin Mart repository for version-controlled storage of all Data Domain Model (DDM) artefacts.</li><li>
Implement DDA-approved modelling standards, naming conventions, and notation frameworks.</li><li>
Validate accessibility and operational readiness of the modelling environment for both onshore and offshore delivery teams.</li></ul><b>
Authoritative Data Register Definition</b><ul><li>
Facilitate stakeholder workshops to identify, scope, and define authoritative data registers.</li><li>
Document domain boundaries, business definitions, ownership, stewardship responsibilities, and relationships with upstream and downstream systems.</li><li>
Produce Authoritative Data Register Definition Packs for each register.</li></ul><b>
Conceptual, Logical and Physical Data Modelling</b><ul><li>
Develop conceptual data models representing high-level entities, relationships, and business rules.</li><li>
Produce supporting Data Requirements Specifications for each conceptual model.</li><li>
Develop logical data models defining entities, attributes, relationships, cardinality, and data types.</li><li>
Ensure traceability between conceptual and logical models using Erwin traceability features.</li><li>
Develop physical data models aligned to ADC&rsquo;s target architecture, including:<ul><li>
IBM DB2 Warehouse schemas.</li><li>
Databricks Delta Lake structures supporting Bronze, Silver, and Gold data pipelines.</li></ul></li><li>
Reverse engineer existing DB2 database structures where required to support reconciliation between current and target-state designs.</li></ul><b>
Data Traceability and Standards Alignment</b><ul><li>
Maintain complete traceability between approved register definitions and conceptual, logical, and physical models.</li><li>
Manage DDM ID Mapping Tables and Erwin Mart version logs.</li><li>
Align data models with the Unified Data Model (UDM) and Government Information Model (GIM).</li><li>
Maintain the GIM/UDM Alignment Register and identify gaps, conflicts, or enhancement opportunities.</li></ul><b>
Integration with Enterprise Data Governance</b><ul><li>
Collaborate with Data Catalogue Specialists to ensure data structures are accurately represented in Microsoft Purview.</li><li>
Support glossary alignment, schema consistency, metadata accuracy, and lineage requirements.</li><li>
Ensure authoritative register entities and attributes are consistently represented across modelling and catalogue platforms.</li></ul><b>
Review, Approval and Compliance</b><ul><li>
Prepare modelling artefacts for formal DDA review and approval.</li><li>
Produce Modelling Approval Packages including:<ul><li>
Erwin exports.</li><li>
DDM ID Mapping Tables.</li><li>
Data Requirements Specifications.</li><li>
GIM/UDM Alignment Register.</li></ul></li><li>
Manage review cycles, incorporate feedback, and maintain version control until formal sign-off is achieved.</li></ul><b>
Physical Model Controls</b><ul><li>
Ensure all physical models include audit columns, logging requirements, and error-handling specifications.</li><li>
Validate physical model structures against Databricks pipeline implementation requirements and enterprise data governance standards.</li></ul><b>
Required Skills and Experience</b><ul><li>
Extensive experience with Erwin Data Modeler and Erwin Mart.</li><li>
Strong background in conceptual, logical, and physical data modelling.</li><li>
Experience with enterprise data governance and metadata management frameworks.</li><li>
Knowledge of IBM DB2 Warehouse and Databricks Delta Lake architectures.</li><li>
Experience implementing data modelling standards and traceability controls.</li><li>
Strong stakeholder engagement and workshop facilitation skills.</li><li>
Understanding of government data standards, information models, and enterprise architecture practices.</li></ul><b>
Deliverables</b><ul><li>
Erwin Mart repository and modelling standards configuration.</li><li>
Authoritative Data Register Definition Packs.</li><li>
Conceptual, logical, and physical data models.</li><li>
Data Requirements Specifications.</li><li>
DDM ID Mapping Tables.</li><li>
GIM/UDM Alignment Register.</li><li>
Modelling Approval Packages and DDA sign-off artefacts.</li></ul><p>
</p><p>0sESuOhEZS</p></div>

Data Modeller (Erwin Data Modeler)

<div><b>Job Description &ndash; Data Quality Engineer (Databricks) &ndash; x 4 Positions</b><br>
<b>Location: Abudhabi - UAE - Onsite</b><br>
<b>Open to Relocate</b><br>
<b>Duration: 6 months ( Extendable to One Year)</b><br>
<b>Experience: 5 to 7 Years</b><br>
<b>Project start date is 1st July - Immediate joiners will be preferred</b><br>
<br>
<b>Role Overview</b><br>
The Data Quality Engineer will be responsible for designing, implementing, and operating ADC's enterprise data quality framework within the Databricks platform. The role will deliver automated profiling, quality rule execution, cleansing, monitoring, remediation support, and quality reporting capabilities across 170 datasets and 1,346 prioritised Critical Data Elements (CDEs).<br>
Working closely with Data Modellers, Data Catalogue Specialists, business data owners, and platform engineers, the Data Quality Engineer will establish scalable and reusable quality controls that improve trust, accuracy, completeness, consistency, timeliness, validity, and uniqueness across ADC's data estate.<br>
<b>Key Responsibilities</b><br>
<b>Databricks Platform Configuration and Administration</b><ul><li>
Configure and manage the Databricks environment supporting enterprise data quality operations.</li><li>
Establish and maintain:<ul><li>
Compute clusters.</li><li>
PySpark notebook frameworks.</li><li>
Delta Lake storage structures.</li><li>
Unity Catalog integration.</li></ul></li><li>
Optimise platform performance for large-scale profiling and rule execution across all in-scope datasets and CDEs.</li><li>
Implement development, testing, and production deployment standards for data quality assets.</li></ul><b>
Data Profiling and Quality Assessment</b><ul><li>
Design and develop AI-assisted profiling notebooks using PySpark.</li><li>
Perform baseline data quality assessments across the six quality dimensions:<ul><li>
Completeness.</li><li>
Accuracy.</li><li>
Consistency.</li><li>
Validity.</li><li>
Timeliness.</li><li>
Uniqueness.</li></ul></li><li>
Capture and analyse:<ul><li>
Null value rates.</li><li>
Duplicate records.</li><li>
Invalid values.</li><li>
Format violations.</li><li>
Outliers.</li><li>
Schema drift.</li></ul></li><li>
Produce quality profiling outputs for all prioritised CDEs and datasets.</li></ul><b>
Data Quality Rule Factory Development</b><ul><li>
Design and implement a reusable Data Quality Rule Factory.</li><li>
Build parameterised PySpark-based rule templates capable of supporting large-scale rule deployment.</li><li>
Enable automated generation and management of approximately 6,730 data quality rules without manual rule-by-rule development.</li><li>
Ensure rules are reusable, configurable, and maintainable across multiple datasets and domains.</li></ul><b>
Data Quality Controls and Pipeline Integration</b><ul><li>
Deploy quality rules as reusable Databricks Jobs integrated into Delta Lake processing pipelines.</li><li>
Embed quality controls within Bronze, Silver, and Gold processing stages.</li><li>
Implement automated quality gates preventing data progression where defined thresholds are not met.</li><li>
Maintain rule traceability and execution history for audit and governance purposes.</li></ul><b>
Data Cleansing and Quality Improvement</b><ul><li>
Develop automated remediation and cleansing pipelines using PySpark.</li><li>
Implement:<ul><li>
Standardisation routines.</li><li>
Data enrichment processes.</li><li>
Deduplication logic.</li><li>
Schema harmonisation controls.</li></ul></li><li>
Deploy machine learning models managed through MLflow for:<ul><li>
Anomaly detection.</li><li>
Exact duplicate detection.</li><li>
Fuzzy matching and duplicate identification.</li></ul></li><li>
Ensure all AI and ML recommendations are explainable, auditable, and routed through human-in-the-loop validation processes where required.</li></ul><b>
Exception Management and Reprocessing</b><ul><li>
Design and manage exception handling processes for failed quality records.</li><li>
Implement quarantine Delta Lake tables serving as the Failed Record Register.</li><li>
Capture and maintain:<ul><li>
Failure reason.</li><li>
Associated CDE.</li><li>
Rule reference.</li><li>
Processing timestamp.</li><li>
Resolution status.</li></ul></li><li>
Develop reprocessing workflows to support correction and controlled re-ingestion of remediated records.</li></ul><b>
Data Quality Metrics and Reporting</b><ul><li>
Develop Delta Lake metric aggregation structures supporting enterprise quality reporting.</li><li>
Calculate and publish:<ul><li>
Data Quality Index (DQI) scores.</li><li>
Dimension-level quality metrics.</li><li>
Rule pass/fail rates.</li><li>
Dataset compliance scores.</li><li>
SLA adherence indicators.</li></ul></li><li>
Provide curated outputs to support Power BI quality dashboards and executive reporting.</li></ul><b>
Monitoring, Alerting and Predictive Quality Management</b><ul><li>
Configure automated quality monitoring and alerting mechanisms.</li><li>
Implement threshold-based notifications using:<ul><li>
Databricks SQL Alerts.</li><li>
Azure Monitor integrations.</li></ul></li><li>
Develop predictive risk scoring models to identify datasets at risk of future quality degradation.</li><li>
Support proactive quality management and operational intervention activities.</li></ul><b>
Root Cause Analysis and Remediation Support</b><ul><li>
Apply Databricks machine learning and pattern analysis techniques to profiling and rule execution outputs.</li><li>
Support AI-assisted root cause analysis across established remediation categories.</li><li>
Identify recurring quality issues, systemic defects, and process breakdowns.</li><li>
Produce prioritised remediation datasets for business and operational stakeholders.</li><li>
Export remediation outputs to Power BI and Excel to support:<ul><li>
Remediation Tiering Matrix.</li><li>
Prioritisation Scoring Models.</li><li>
Governance reporting processes.</li></ul></li></ul><b>
Governance, Compliance and Stakeholder Engagement</b><ul><li>
Collaborate with Data Modellers and Data Catalogue Specialists to ensure quality controls align with authoritative data definitions and metadata standards.</li><li>
Support DDA and DGE governance processes by producing required quality artefacts and evidence.</li><li>
Maintain documentation, version control, and audit trails for all quality assets, rules, models, and processes.</li><li>
Participate in quality reviews, governance forums, and stakeholder workshops.</li></ul><b>
Required Skills and Experience</b><ul><li>
Strong experience designing and implementing enterprise Data Quality frameworks.</li><li>
Advanced Databricks engineering experience.</li><li>
Strong PySpark development skills.</li><li>
Experience with:<ul><li>
Delta Lake.</li><li>
Unity Catalog.</li><li>
Databricks Workflows and Jobs.</li><li>
Databricks SQL.</li></ul></li><li>
Experience building scalable data validation and quality rule frameworks.</li><li>
Knowledge of machine learning techniques for anomaly detection and data quality monitoring.</li><li>
Experience using MLflow for model management and deployment.</li><li>
Strong understanding of data governance, metadata management, and data lifecycle processes.</li><li>
Experience integrating data quality metrics into reporting platforms such as Power BI.</li><li>
Knowledge of cloud-based data engineering and modern lakehouse architectures.</li></ul><b>
Deliverables</b><ul><li>
Configured Databricks Data Quality environment.</li><li>
Enterprise Data Quality Rule Factory.</li><li>
AI-assisted profiling notebooks and baseline assessment outputs.</li><li>
Automated data quality validation and gating processes.</li><li>
Data cleansing and remediation pipelines.</li><li>
Failed Record Register and reprocessing workflows.</li><li>
Data Quality metric aggregation tables.</li><li>
DQI reporting feeds and dashboard datasets.</li><li>
Predictive quality monitoring and alerting solutions.</li><li>
Root Cause Analysis and remediation support datasets.</li><li>
Governance, audit, and compliance artefacts supporting DDA and DGE reviews.</li></ul><p>
</p><p>dmGrkjT88v</p></div>

Data Quality Engineer (Databricks)

<div><b>Position Title : Delivery Manager &ndash; Data, BI &amp; AI</b><br>
<b>Experience Required: </b>6&ndash;8 Years (Should be open to Travel)<br>
<b>Employment Type :</b>Full-Time - Riyadh - Onsite<br>
<br>
<b>Job Overview</b><br>
We are looking for an experienced Delivery Manager to lead the successful execution and delivery of Data, Business Intelligence (BI), and AI-driven projects. The ideal candidate will have a strong background in managing cross-functional technical teams, driving client engagement, ensuring project governance, and delivering scalable analytics and AI solutions within timelines and budget.<br>
The role requires a combination of project delivery expertise, stakeholder management, technical understanding, and operational leadership.<br>
<br>
<b>Key Responsibilities</b><ul><li>
Lead end-to-end delivery of Data Engineering, BI, Analytics, and AI/ML projects.</li><li>
Manage project planning, execution, resource allocation, risk management, and delivery governance.</li><li>
Collaborate with business stakeholders, technical teams, architects, and clients to define project scope and delivery roadmap.</li><li>
Ensure successful implementation of data platforms, dashboards, reporting systems, predictive analytics, and AI solutions.</li><li>
Drive Agile/Scrum ceremonies and ensure timely sprint execution and milestone tracking.</li><li>
Monitor project KPIs, delivery quality, utilization, and customer satisfaction.</li><li>
Manage multiple concurrent projects while maintaining delivery excellence.</li><li>
Coordinate with engineering, QA, DevOps, cloud, and analytics teams for seamless project execution.</li><li>
Identify delivery risks, dependencies, and mitigation strategies proactively.</li><li>
Support pre-sales activities including solution discussions, estimations, project planning, and proposal reviews.</li><li>
Establish best practices for delivery management, documentation, reporting, and communication.</li><li>
Mentor team leads and project teams to improve execution efficiency and performance.</li></ul><b>
Required Skills &amp; Expertise</b><ul><li>
Proven experience delivering <b>Data, BI, Analytics, and AI/ML projects</b>.</li><li>
Strong understanding of:<ul><li>
Data Warehousing &amp; ETL</li><li>
Business Intelligence platforms</li><li>
Cloud Data Platforms</li><li>
AI/ML solution lifecycle</li><li>
Reporting &amp; Analytics frameworks</li></ul></li><li>
Experience working with tools/technologies such as:<ul><li>
Power BI, Tableau, Looker, or Qlik</li><li>
SQL &amp; Data Modeling</li><li>
Azure, AWS, or GCP</li><li>
Data Lakes / Data Warehouses</li><li>
AI/ML project coordination</li></ul></li><li>
Strong knowledge of Agile, Scrum, and project management methodologies.</li><li>
Excellent stakeholder management and client communication skills.</li><li>
Experience managing distributed or cross-functional technical teams.</li><li>
Ability to handle delivery escalations, priorities, and deadlines effectively.</li></ul><b>
Preferred Qualifications</b><ul><li>
Bachelor&rsquo;s degree in Computer Science, Software Engineering, Data Science, or related field.</li><li>
PMP, Scrum Master, or Agile certifications are a plus.</li><li>
Exposure to enterprise-scale analytics or AI transformation projects is highly preferred.</li></ul><p>
</p><p>4TcsbdWlbr</p></div>

Delivery Manager (Data, BI & AI Projects)

<div><b>Position Title : AI/ML Engineer &ndash; Agentic AI</b><br>
<b>Experience Required: </b>4&ndash;6 Years (Should be open to Travel)<br>
<b>Employment Type : </b>Full-Time - Riyadh - Onsite<br>
<br>
<b>Job Overview</b><br>
We are seeking a highly skilled AI/ML Engineer with hands-on experience in building intelligent AI systems, machine learning models, and Agentic AI solutions. The ideal candidate will have strong expertise in designing, developing, and deploying AI-powered applications leveraging LLMs, autonomous agents, orchestration frameworks, and modern ML techniques.<br>
The role requires a strong engineering mindset, practical AI implementation experience, and the ability to work across the full AI/ML lifecycle from experimentation to production deployment.<br>
<br>
<b>Key Responsibilities</b><ul><li>
Design, develop, and deploy AI/ML solutions for real-world business use cases.</li><li>
Build and optimize <b>Agentic AI systems</b> using LLMs, autonomous workflows, and multi-agent architectures.</li><li>
Develop machine learning models for prediction, classification, recommendation, NLP, and automation tasks.</li><li>
Work with orchestration frameworks such as LangChain, CrewAI, AutoGen, LangGraph, or similar technologies.</li><li>
Integrate AI agents with APIs, databases, enterprise systems, and third-party tools.</li><li>
Fine-tune, evaluate, and optimize Large Language Models (LLMs).</li><li>
Develop Retrieval-Augmented Generation (RAG) pipelines and vector search implementations.</li><li>
Collaborate with data engineers, software developers, and product teams to deliver scalable AI solutions.</li><li>
Perform prompt engineering, model experimentation, and performance optimization.</li><li>
Ensure AI solutions are production-ready, scalable, secure, and cost-efficient.</li><li>
Monitor model performance, drift, and continuous improvement processes.</li><li>
Stay updated with emerging AI, Generative AI, and Agentic AI trends and technologies.</li></ul><b>
Required Skills &amp; Expertise</b><ul><li>
Strong hands-on experience in <b>Machine Learning, Generative AI, and Agentic AI development</b>.</li><li>
Proficiency in Python and AI/ML development frameworks.</li><li>
Experience with:<ul><li>
LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks</li><li>
OpenAI, Anthropic, Gemini, or open-source LLMs</li><li>
RAG architectures and Vector Databases</li><li>
Prompt Engineering &amp; AI workflow automation</li></ul></li><li>
Solid understanding of:<ul><li>
NLP concepts</li><li>
ML algorithms and model evaluation</li><li>
Deep Learning fundamentals</li><li>
AI model deployment and inference optimization</li></ul></li><li>
Experience with ML libraries/frameworks such as:<ul><li>
PyTorch</li><li>
TensorFlow</li><li>
Scikit-learn</li><li>
Hugging Face Transformers</li></ul></li><li>
Experience with cloud platforms such as Azure, AWS, or GCP is preferred.</li><li>
Familiarity with Docker, APIs, CI/CD, and MLOps practices.</li><li>
Strong problem-solving and analytical skills.</li></ul><b>
Preferred Qualifications</b><ul><li>
Bachelor&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, or related field.</li><li>
Experience working on enterprise AI automation or AI assistant platforms is highly preferred.</li><li>
Exposure to AI governance, evaluation frameworks, and AI observability tools is a plus.</li></ul><br>
<p>
</p><p>tTAmIvfFVv</p></div>

AI/ML Engineer – Agentic AI

Join Datamatics Global Services Ltd and explore 7   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.