planning engineer

senior data engineer

ai engineer

architect

architectural draftsman

data architect

Jorofy Private Limited

ENUM is Hiring in Oman | Enterprise System Architect &amp; Digital Transformation Consultant (On-Site)We are looking for a highly experienced professional to lead enterprise architecture and digital transformation initiatives across government and enterprise environments.Enterprise System Architect &amp; Digital Transformation ConsultantLocation: Oman (On-site)Key Skills &amp; Experience:✔ Enterprise Architecture &amp; Solution Design (TOGAF preferred) ✔ Microsoft .NET, Azure, Microservices &amp; API-first architecture ✔ AI/ML integration, LLMs, RAG, and intelligent systems design ✔ DevOps, CI/CD pipelines, Docker &amp; cloud-native practices ✔ Enterprise integration, system modernization &amp; governance ✔ Experience in government or large-scale enterprise projectsKey Responsibilities:✔ Design scalable and secure enterprise architectures ✔ Lead digital transformation and modernization initiatives ✔ Architect AI-enabled and data-driven platforms ✔ Define integration frameworks and technical standards ✔ Oversee end-to-end software engineering and deliveryInterested candidates may share their CV at: careers@enums.coCandidates with GCC or government project experience will be preferred.#Hiring #OmanJobs #EnterpriseArchitecture #DigitalTransformation #MicrosoftAzure #DotNet #AI #SystemArchitecture #TechnologyJobsEducation:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>Enterprise Architecture &amp; Solution Design : 10 years (Required)</li></ul>Work Location: In person

Enterprise System Architect & Digital Transformation Consultant

Group AMANA

<div>
 
 Amana is seeking an experienced Data Platform Lead with deep expertise in Databricks, the Microsoft Azure ecosystem, and modern lakehouse architectures. The ideal candidate will play a central role in Amana's ongoing platform refresh, moving workloads from Synapse Analytics to a Databricks lakehouse with Unity Catalog, and building the technical foundation that powers analytics, AI, and governance across the enterprise. This role sits within Amana's Data Science, Governance &amp; AI Centre of Excellence, working alongside architects, engineers, analysts, data scientists, and AI engineers, with future growth opportunities into senior platform leadership.
 
 
 
 
 
 
 Why This Role Matters
 
 
 
 Amana operates across capital-intensive sectors where data reliability, cost discipline, and speed of insight are business-critical. The enterprise data platform is the backbone of every downstream analytics, AI, and governance initiative &mdash; from ERP-integrated reporting and predictive models to Agentic AI and Copilot rollouts across the group.
 
 
 You will be at the technical centre of this transformation, designing, building, and hardening the lakehouse that the rest of the function depends on.
 
 
 
 
 
 
 Core Responsibilities
 
 
 
 
 Lakehouse Architecture &amp; Delivery
 
 
 <ul>
 <li>
 Design and deliver end-to-end Databricks lakehouse components &mdash; ingestion, transformation, semantic layer, and serving.
 </li>
 <li>
 Set and enforce Delta Lake and medallion architecture standards across bronze, silver, and gold layers.
 </li>
 <li>
 Lead the technical execution of the Synapse Analytics to Databricks migration, including parallel run, cutover, and decommissioning.
 </li>
 <li>
 Contribute to and sign off on reference designs, integration patterns, and architecture decision records.
 </li>
 </ul>
 
 
 
 
 
 Data Engineering &amp; Integration
 
 
 <ul>
 <li>
 Build and maintain robust ingestion and transformation pipelines from Amana's core enterprise systems: Oracle Fusion (Finance, HCM, P2P, CRM), Hyperion, CMiC, project and operations systems, SharePoint, and Power Platform.
 </li>
 <li>
 Apply strong CI/CD, DataOps, and infrastructure-as-code practices using Git, Azure DevOps, and Terraform or Bicep.
 </li>
 <li>
 Ensure platform reliability through monitoring, alerting, and structured incident response.
 </li>
 </ul>
 
 
 
 
 
 AI/ML &amp; Analytics Enablement
 
 
 <ul>
 <li>
 Build and operate feature store, MLOps, and LLMOps foundations on Databricks.
 </li>
 <li>
 Enable production-grade RAG, agent, and Copilot patterns in partnership with the Data Scientist and AI Engineer.
 </li>
 <li>
 Deliver Power BI semantic models, certified datasets, and self-service guardrails supporting the Amana Digital Academy and enterprise adoption.
 </li>
 </ul>
 
 
 
 
 
 Data Governance &amp; Trustworthy Data
 
 
 <ul>
 <li>
 Implement lineage, cataloguing, access control, data quality, and PDPL controls inside the platform using Unity Catalog and Microsoft Purview.
 </li>
 <li>
 Partner with the Data Governance Office to translate live policies into enforceable platform controls.
 </li>
 <li>
 Support regulatory, ethical, and internal compliance obligations across the data estate.
 </li>
 </ul>
 
 
 
 
 
 Cloud &amp; Cost Discipline
 
 
 <ul>
 <li>
 Own FinOps hygiene on the platform: cluster policies, workload tiering, rightsizing, and chargeback readiness.
 </li>
 <li>
 Translate cloud cost outcomes into commercial terms understood by finance and business stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Collaboration &amp; Technical Leadership
 
 
 <ul>
 <li>
 Work closely with the Data Architect, Data Engineer, Data Analyst, Data Scientist, and AI Engineer to set and uphold technical standards.
 </li>
 <li>
 Provide hands-on technical guidance and code review across the team.
 </li>
 <li>
 Translate business requirements into technical designs with clear delivery outcomes.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 Minimum of 7 years in data engineering or data platform work, with strong hands-on delivery experience.
 </li>
 <li>
 At least 3 years hands-on with Databricks, Apache Spark, and Delta Lake at enterprise scale. Snowflake or BigQuery experience is acceptable where the CV shows a real Databricks migration.
 </li>
 <li>
 Contributed to the build or rebuild of an enterprise data platform serving multiple business domains.
 </li>
 <li>
 Deep hands-on experience with the Azure data stack: Databricks, ADLS, Azure Data Factory, Synapse, Azure SQL, Fabric.
 </li>
 <li>
 Direct experience integrating heavy ERP sources: Oracle Fusion, Hyperion, CMiC, or equivalent estates.
 </li>
 <li>
 Governance shipped to production using Unity Catalog or Microsoft Purview, with PDPL or GDPR controls operational, not theoretical.
 </li>
 <li>
 Practical FinOps outcomes on cloud spend.
 </li>
 <li>
 Strong on CI/CD, Git, Azure DevOps, and infrastructure-as-code (Terraform or Bicep).
 </li>
 <li>
 Excellent written and verbal communication skills across technical and business audiences.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Direct experience of a Synapse Analytics to Databricks migration.
 </li>
 <li>
 Exposure to MLOps and LLMOps stacks: MLflow, feature store, vector stores, RAG, agent frameworks.
 </li>
 <li>
 Familiarity with Power BI semantic models and enterprise BI governance.
 </li>
 <li>
 Streaming and event-driven experience: Kafka, Event Hubs, Structured Streaming.
 </li>
 <li>
 Multi-entity, multi-country group exposure with mixed data residency considerations.
 </li>
 <li>
 Industry experience in construction, engineering services, manufacturing, energy, or logistics.
 </li>
 </ul>
 
 
 
 
 
 Certifications
 
 
 
 
 
 Mandatory:
 
 
 
 <ul>
 <li>
 
 Databricks Certified Data Engineer Professional
 
 (Candidates holding the Associate level will be considered on the condition that Professional is achieved within 6 months of joining.)
 </li>
 </ul>
 
 
 Preferred (one or more):
 
 
 <ul>
 <li>
 
 Databricks Certified Machine Learning Professional
 
 </li>
 <li>
 
 Databricks Certified Generative AI Engineer Associate
 
 </li>
 <li>
 
 Microsoft Certified: Azure Data Engineer Associate
 
 (DP-203 / DP-700)
 </li>
 <li>
 
 Microsoft Certified: Fabric Analytics Engineer Associate
 
 (DP-600)
 </li>
 <li>
 
 Microsoft Certified: Azure Solutions Architect Expert
 
 </li>
 <li>
 
 Certified Data Management Professional (CDMP)
 
 &mdash; DAMA
 </li>
 </ul>
 
 
 Education
 
 
 
 M.Tech / B.E. / B.Tech (Computer Science, Information Systems, IT) / MCA / MCS.
 
</div>

Data Platform Lead

Datamatics Global Services Ltd

<div>Job Description &ndash; 1 x Data Modeller (Erwin Data Modeler) 
Location: Abudhabi - UAE - Onsite 
Open to Relocate 
Duration: 6 months ( Extendable to One Year) 
Experience: 5 to 7 Years 
Project start date is 1st July - Immediate joiners will be preferred 
 
Role Overview 
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. 
 
Key Responsibilities 
Erwin Environment Setup and Governance<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>
Authoritative Data Register Definition<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>
Conceptual, Logical and Physical Data Modelling<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>
Data Traceability and Standards Alignment<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>
Integration with Enterprise Data Governance<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>
Review, Approval and Compliance<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>
Physical Model Controls<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>
Required Skills and Experience<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>
Deliverables<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>
0sESuOhEZS</div>

Data Modeller (Erwin Data Modeler)

MultiBank Group

<div>
 
 Welcome to
 
 MultiBank Group
 
 , a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.
 
 
 
 
 
 Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.
 
 
 
 
 
 
 Role Overview:
 
 
 
 
 
 
 We are seeking an experienced
 
 AI Data Engineer
 
 to design, develop, and deploy innovative data and machine learning solutions that drive customer engagement, retention, and lifetime value (LTV). This role will focus on building scalable data pipelines, predictive models, and GenAI-powered applications that enable more personalised trading experiences and support data-driven decision-making across the business.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 
 <ul>
 <li>
 Collaborate with the wider marketing department to build meaningful datasets and a centralised data warehouse that will be used for reporting across numerous teams, focused on customer retention and LTV.
 </li>
 <li>
 Develop and own machine learning solutions that specialise in customer personalisation to increase engagement and coordinate with marketing teams towards their strategy and execution across multiple channels, especially around predictive modelling, churn prediction and customer segmentation.
 </li>
 <li>
 Explore the capabilities of Gen AI to develop new apps for our traders that make trading easier and more personalised based on their preferences.
 </li>
 <li>
 Maintain a commercial acumen and find opportunities where technology can be used to increase customer engagement or automate internal tasks.
 </li>
 </ul>
 
 
 
 
 
 Qualifications &amp; Requirements:
 
 
 
 
 
 <ul>
 <li>
 Strong expertise in SQL, comfortable with raw data and multiple high-volume datasets such as customer journey, marketing performance or product behaviour.
 </li>
 <li>
 Comfortable creating pipelines and automations with Python to connect multiple endpoints and APIs such as first party databases, marketing platforms or other data collection platforms.
 </li>
 <li>
 Expertise in using Python todeploy machine learning solutions end to end, especially around predictive modelling and customer segmentation.
 </li>
 <li>
 Previous experience in finding customer insights through data analysis, communicating it to different stakeholders and strategizing on how to increase customer engagement and LTV.
 </li>
 <li>
 Capable of creating applications using LLMs that summarise high volumes of data and knowledge of the latest Gen AI use cases.
 </li>
 <li>
 Previous exposure to
 
 ETL tools
 
 (e.g., dbt, AWS Glue) and cloud environments (preferably
 
 AWS, SageMaker
 
 ).
 </li>
 <li>
 Strong communication skills with the ability to present complex data insights to non-technical stakeholders and support business strategy.
 </li>
 </ul>
 
 
 
 
 
 Why Join Us?
 
 
 
 
 
 <ul>
 <li>
 Work with an industry-leading global financial institution.
 </li>
 <li>
 Competitive salary and comprehensive employee benefits.
 </li>
 <li>
 Opportunities for professional growth and career advancement.
 </li>
 <li>
 Collaborative, inclusive, and dynamic work environment.
 </li>
 <li>
 Commitment to innovation and professional excellence.
 </li>
 </ul>
 
 
 
 
 
 Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
 
 
</div>

AI Data Engineer

Arcsen

<div>The Firm:
Arcsen is a leading global technology consulting firm specializing in providing innovative solutions and expert guidance to businesses across EMEA. With a commitment to excellence, Arcsen partners with industry giants such as Salesforce, MuleSoft, Tableau, Slack, and Sprout, Certinia, and Splunk, ensuring clients receive top-tier services tailored to their unique needs.
Job Description:
As a Salesforce Technical Architect at Arcsen, you will play a pivotal role in the design, development, and deployment of Salesforce solutions. You will collaborate closely with stakeholders to understand business requirements and translate them into technical designs that leverage the full power of the Salesforce platform. This role requires strong technical expertise, leadership abilities, and a deep understanding of Salesforce architecture principles.
Responsibilities:<ul><li>Design and architect end-to-end technical solutions on the Salesforce platform, ensuring alignment with business objectives and Salesforce best practices.</li><li>Collaborate with stakeholders to gather and analyze requirements, translating them into scalable Salesforce solutions.</li><li>Provide expert guidance and leadership to development teams throughout the project lifecycle.</li><li>Mentor and coach developers on Salesforce development best practices, conducting code reviews and ensuring high-quality deliverables.</li><li>Architect and implement integrations between Salesforce and other enterprise systems, ensuring data integrity and seamless flow of information.</li><li>Manage data migration and data quality initiatives, adhering to industry standards and compliance requirements.</li><li>Define and enforce Salesforce governance policies, security controls, and compliance standards.</li><li>Create comprehensive technical documentation including solution architecture diagrams, design specifications, and deployment plans.</li><li>Effectively communicate technical solutions and strategies to non-technical stakeholders.</li><li>Stay current with Salesforce platform updates, features, and industry trends, providing recommendations for continuous improvement and optimization.</li><li>Drive innovation and efficiency within Salesforce implementations through Agile methodologies and DevOps practices.</li></ul> 
Requirements 
<ul><li>
Bachelor&rsquo;s degree in Computer Science, Engineering, or a related field (or equivalent work experience).</li><li>
Minimum of 4 years of experience designing and implementing Salesforce solutions, with a proven track record of successful project delivery.</li><li>
Experience in a technical leadership role, overseeing Salesforce development teams and driving technical excellence.</li><li>
Expertise in Salesforce configuration, customization (Apex, Visualforce), and Lightning component development.</li><li>
Proficiency in Salesforce integration patterns and tools (e.g., REST, SOAP, APIs, MuleSoft, Informatica).</li><li>
Strong understanding of Salesforce data model, security model, and declarative capabilities.</li><li>
Exceptional communication skills with the ability to articulate complex technical solutions to diverse audiences.</li><li>
Strong leadership and interpersonal skills, with a collaborative approach to problem-solving.</li><li>
Ability to manage multiple priorities in a dynamic, fast-paced environment.</li></ul> 

Benefits 
<ul><li>
Competitive salary and benefits package.</li><li>
Collaborative and supportive work environment.</li><li>
Career growth opportunities.</li></ul>
Arcsen is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Different makes us better.
By applying, you give your consent to the processing of your personal data which are necessary to the Personal Data Administrator for the purpose of the recruitment process, and the future recruitment processes. This consent will allow us to contact you in connection with our recruitment. We will process your data for two years.</div>

Salesforce Technical Architect

Times World Information Technology

<div>We are looking for a Senior Data &amp; AI Platform Engineer with strong expertise in data architecture, database design, and scalable system development. The ideal candidate should have a deep understanding of data engineering concepts, modern data platforms, and the ability to design robust, scalable back-end systems and data pipelines.
<div><h4 class="jobSectionHeader">Key responsibilities:</h4>
<ul><li>Design and develop scalable back-end systems</li><li>
Define and implement data architecture and database design strategies</li><li>
Build and optimize data ingestion and transformation pipelines
</li><li>Develop and maintain unified data models across multiple systems
</li><li>Design end-to-end data flows and integration strategies
</li><li>Collaborate with cross-functional teams to ensure efficient data handling and processing
</li><li>Ensure system scalability, performance, and reliability</li></ul><h4 class="jobSectionHeader">
Machine Learning &amp; AI Integration</h4><ul><li>
Work closely with the AI/ML team to understand data requirements for model training, feature engineering, and pipeline development
</li><li>Prepare, validate, and deliver clean, structured data to support AI/ML systems and intelligent workflows
</li><li>Consume and integrate outputs from ML models into data pipelines and backend systems
</li><li>Maintain awareness of ML concepts to effectively collaborate with AI/analytics teams</li></ul><h4 class="jobSectionHeader">
Core Technical Skills</h4><ul><li>
Back-end &amp; System Design</li><li>
Expertise in system scalability and performance optimization
</li><li>Solid understanding of distributed systems and back-end architecture
</li><li>Data Engineering Concepts (IMPORTANT)</li><li>
Strong knowledge of data modelling (OLTP vs OLAP)
</li><li>Strong knowledge of data lake architecture (primary) and data warehousing concepts</li><li>
Strong knowledge of REST APIs and API design (FastAPI / Flask / Django)</li></ul><h4 class="jobSectionHeader">
Core Platforms &amp; Technologies (Required)</h4>
Strong working knowledge of:<ul><li>
 Relational databases - strong hands-on experience required (e.g. PostgreSQL, MS SQL Server, MySQL)</li><li>
Non-relational / NoSQL databases - working knowledge required (e.g. MongoDB, SQLite, TimescaleDB, Redis)</li><li>
Graph databases - understanding of graph data models (e.g. Apache AGE, Neo4j concepts)</li><li>
Comfortable working across multi-database environments - relational, time-series, graph, and cache layers in a single architecture</li></ul>
Good to Have: Hands-on experience with modern data tools such as Kafka, Airbyte, S3/ADLS, Snowflake, or similar platforms<h4 class="jobSectionHeader">
Data Ingestion &amp; Processing</h4>
Ability to design and implement:<ul><li>
Data ingestion pipelines
</li><li>Data transformation layers (ETL/ELT)
</li><li>Unified and scalable data models
</li><li>System Thinking &amp; Architecture</li></ul>
Ability to:<ul><li>
Design scalable back-end architectures
</li><li>Define and manage data flow across systems
</li><li>Guide integration strategies between multiple services and platforms</li></ul>
Good to Have<ul><li>
Experience with cloud platforms (AWS / GCP / Azure)
</li><li>Exposure to real-time data processing systems
</li><li>Knowledge of ML data pipelines or analytics workflows
</li><li>Experience using Python for data ingestion pipelines, transformation scripts, and automation workflows is an advantage</li></ul>
What We&rsquo;re Looking For<ul><li>
Passion for experimenting with new tools, frameworks, and ideas
</li><li>Ability to quickly prototype and iterate on features
</li><li>Interest in blending creativity with engineering
</li><li>Comfort working in less rigid, exploratory development environments
</li><li>Strong curiosity and self-learning mindset</li></ul>
Bonus Points If You<ul><li>
Use AI-assisted coding tools (like GitHub Copilot, Cursor, Antigravity, Claude)
</li><li>Build side projects, prototypes, or experimental apps
</li><li>Enjoy rapid MVP development, or creative coding
</li><li>Stay updated with latest trends in AI, and developer tools</li></ul> 

</div><div><h4 class="jobSectionHeader">Requirements (Qualifications/Experience/Competencies)
</h4>Bachelor's degree in Computer Science, Information Technology, Software Engineering, Data Science, or a related field. A Master's degree in a relevant field is an advantage 
 
5 - 7 years of experience
Ready to Join Us? 
 
If you are passionate about building modern AI-powered products and enjoy working on innovative digital solutions, we would love to hear from you. Immediate joiners are preferred. 
 
Please note: This position is open to candidates currently residing in the UAE only.</div></div>

Senior Data & AI Platform Engineer

Timesworld

<div>
 Job ID: PRJ-DXB-245
 
 
 Department: Product Development
 
 
 Job Type: Permanent
 
 
 Location: Dubai
 
 
 Job Details
 
 
 We are looking for a Senior Data &amp; AI Platform Engineer with strong expertise in data architecture, database design, and scalable system development. The ideal candidate should have a deep understanding of data engineering concepts, modern data platforms, and the ability to design robust, scalable back-end systems and data pipelines.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design and develop scalable back-end systems
 </li>
 <li>
 Define and implement data architecture and database design strategies
 </li>
 <li>
 Build and optimize data ingestion and transformation pipelines
 </li>
 <li>
 Develop and maintain unified data models across multiple systems
 </li>
 <li>
 Design end-to-end data flows and integration strategies
 </li>
 <li>
 Collaborate with cross-functional teams to ensure efficient data handling and processing
 </li>
 <li>
 Ensure system scalability, performance, and reliability
 
 
 </li>
 </ul>
 Machine Learning &amp; AI Integration
 
 
 <ul>
 <li>
 Work closely with the AI/ML team to understand data requirements for model training, feature engineering, and pipeline development
 </li>
 <li>
 Prepare, validate, and deliver clean, structured data to support AI/ML systems and intelligent workflows
 </li>
 <li>
 Consume and integrate outputs from ML models into data pipelines and backend systems
 </li>
 <li>
 Maintain awareness of ML concepts to effectively collaborate with AI/analytics teams
 
 
 </li>
 </ul>
 Core Technical Skills
 
 
 <ul>
 <li>
 Back-end &amp; System Design
 </li>
 <li>
 Expertise in system scalability and performance optimization
 </li>
 <li>
 Solid understanding of distributed systems and back-end architecture
 </li>
 <li>
 Data Engineering Concepts (IMPORTANT)
 </li>
 <li>
 Strong knowledge of data modelling (OLTP vs OLAP)
 </li>
 <li>
 Strong knowledge of data lake architecture (primary) and data warehousing concepts
 </li>
 <li>
 Strong knowledge of REST APIs and API design (FastAPI / Flask / Django)
 
 
 </li>
 </ul>
 Core Platforms &amp; Technologies (Required)
 
 
 
 Strong Working Knowledge Of
 
 
 
 <ul>
 <li>
 Relational databases - strong hands-on experience required (e.g. PostgreSQL, MS SQL Server, MySQL)
 </li>
 <li>
 Non-relational / NoSQL databases - working knowledge required (e.g. MongoDB, SQLite, TimescaleDB, Redis)
 </li>
 <li>
 Graph databases - understanding of graph data models (e.g. Apache AGE, Neo4j concepts)
 </li>
 <li>
 Comfortable working across multi-database environments - relational, time-series, graph, and cache layers in a single architecture
 
 
 </li>
 </ul>
 Good to Have: Hands-on experience with modern data tools such as Kafka, Airbyte, S3/ADLS, Snowflake, or similar platforms
 
 
 Data Ingestion &amp; Processing
 
 
 
 Ability To Design And Implement
 
 
 
 <ul>
 <li>
 Data ingestion pipelines
 </li>
 <li>
 Data transformation layers (ETL/ELT)
 </li>
 <li>
 Unified and scalable data models
 </li>
 <li>
 System Thinking &amp; Architecture
 
 
 </li>
 </ul>
 
 Ability To
 
 
 
 <ul>
 <li>
 Design scalable back-end architectures
 </li>
 <li>
 Define and manage data flow across systems
 </li>
 <li>
 Guide integration strategies between multiple services and platforms
 
 
 </li>
 </ul>
 
 Good to Have
 
 
 
 <ul>
 <li>
 Experience with cloud platforms (AWS / GCP / Azure)
 </li>
 <li>
 Exposure to real-time data processing systems
 </li>
 <li>
 Knowledge of ML data pipelines or analytics workflows
 </li>
 <li>
 Experience using Python for data ingestion pipelines, transformation scripts, and automation workflows is an advantage
 
 
 </li>
 </ul>
 
 What We&rsquo;re Looking For
 
 
 
 <ul>
 <li>
 Passion for experimenting with new tools, frameworks, and ideas
 </li>
 <li>
 Ability to quickly prototype and iterate on features
 </li>
 <li>
 Interest in blending creativity with engineering
 </li>
 <li>
 Comfort working in less rigid, exploratory development environments
 </li>
 <li>
 Strong curiosity and self-learning mindset
 
 
 </li>
 </ul>
 
 Bonus Points If You
 
 
 
 <ul>
 <li>
 Use AI-assisted coding tools (like GitHub Copilot, Cursor, Antigravity, Claude)
 </li>
 <li>
 Build side projects, prototypes, or experimental apps
 </li>
 <li>
 Enjoy rapid MVP development, or creative coding
 </li>
 <li>
 Stay updated with latest trends in AI, and developer tools
 
 
 </li>
 </ul>
 
 Requirements (Qualifications/Experience/Competencies)
 
 
 
 Bachelor's degree in Computer Science, Information Technology, Software Engineering, Data Science, or a related field. A Master's degree in a relevant field is an advantage
 
 
 5 - 7 years of experience
 
 
 
 Ready to Join Us?
 
 
 
 If you are passionate about building modern AI-powered products and enjoy working on innovative digital solutions, we would love to hear from you. Immediate joiners are preferred.
 
 
 
 Please note: This position is open to candidates currently residing in the UAE only.
 
</div>

Explore 439+ Data architect in Dubai this July. Find roles across top companies and apply now to boost your career.

439 data architect jobs In Dubai

Enterprise System Architect & Digital Transformation Consultant

Data Platform Lead

Data Modeller (Erwin Data Modeler)

AI Data Engineer

Salesforce Technical Architect

Senior Data & AI Platform Engineer

Senior Data & AI Platform Engineer