34 Data Architect jobs in the United Arab Emirates

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Position Overview

The Data Architect is responsible for designing, implementing, and maintaining an organization's data architecture and strategy, ensuring that data is collected, stored, and processed efficiently and securely to support business intelligence, data analytics, and machine learning operations (MLOps) practices.

Key Responsibilities

• Designing Data Architecture : Plan and implement a robust, scalable data architecture that integrates data from various sources and supports diverse analytical needs, while optimising costs and meeting business requirements.
• Implementing Data Engineering Pipelines : Design and develop data pipelines for data extraction, transformation, and loading (ETL) processes, ensuring data quality and consistency.
• Enabling Data Intelligence and Analytics : Build and maintain data warehouses, data marts, and data lakes to support business intelligence and data analytics initiatives.
• Supporting MLOps Practices : Collaborate with data scientists and machine learning engineers to design and implement data infrastructure and processes that support machine learning model development, deployment, and maintenance.
• Ensuring Data Security and Compliance : Implement security measures, policies, and procedures to safeguard data privacy and comply with relevant regulations.
• Data Governance and Management : Establish and enforce data governance policies and standards to ensure data quality, integrity, and accessibility.
• Collaborating with Cross-Functional Teams : Work closely with data engineers, data scientists, business analysts, and other stakeholders to understand data requirements and translate them into technical solutions.
• Staying Abreast of Technological Advancements : Keep up-to-date with emerging technologies and trends in data architecture, data engineering, and MLOps to identify opportunities for improvement and innovation.
• Optimising Data Performance : Monitor and analyze data processing performance, identify bottlenecks, and implement optimisations to enhance efficiency and scalability.
• Documentation and Knowledge Sharing : Create and maintain comprehensive documentation of data architecture, models, and processing workflows.

Technical Requirements

• Extensive experience in data architecture design and implementation.
• Hands-on experience with Amazon Redshift for data warehousing, query optimization, and integration with AWS analytics services.
• Strong knowledge of data engineering principles and practices.
• Expertise in data warehousing, data modelling, and data integration.
• Experience in MLOps and machine learning pipelines.
• Proficiency in SQL and data manipulation languages.
• Experience with big data platforms (including PowerBI, DBT, Databricks, MySQL, Postgres, Clickhouse, Kafka, Redis etc) and cloud-based infrastructure on AWS.

Education & Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent experience.
• Preferred certifications (optional) :
• AWS Machine Learning Ops Engineer

Seniority level

Seniority level

Not Applicable

Employment type

Employment type

Full-time

Job function

Job function

Engineering and Information Technology

Software Development, Data Infrastructure and Analytics, and IT System Custom Software Development

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Business Data & AI Analyst(Arabic speaking)

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Job Overview:

We are seeking an experienced Data Engineer to design, implement, and optimize data pipelines and infrastructure to support our advanced AI systems.

• Pipeline Development :

Design, develop, and maintain scalable and reliable data pipelines to ingest, transform, and load diverse datasets from various sources, including structured and unstructured data, streaming data, and real-time feeds.

• Data Integration :

Implement robust data integration processes to seamlessly integrate data from different sources, ensuring consistency, reliability, and data quality for analytics and AI use cases.

• Data Storage :

Design and optimize data storage solutions, including relational databases, NoSQL databases, data lakes, and cloud storage services, to efficiently store and manage large volumes of data for AI and machine learning model consumption.

• Performance Optimization :

Optimize data processing and query performance to enhance system scalability, reliability, and efficiency, leveraging techniques such as indexing, partitioning, caching, and parallel processing—especially for AI model training and inference pipelines.

• Data Governance :

Implement data governance frameworks to ensure data security, privacy, integrity, and compliance with regulatory requirements, including data encryption, access controls, and auditing—crucial for responsible AI deployment.

• Monitoring and Maintenance :

Monitor data pipelines and infrastructure components, proactively identify and address issues, and perform routine maintenance tasks to ensure system stability and reliability across AI and data science environments.

• Collaboration :

Collaborate closely with cross-functional teams, including data scientists, ML engineers, architects, and domain experts, to understand AI/ML requirements, gather insights, and deliver integrated, production-ready data solutions.

• Documentation :

Create comprehensive documentation, including technical specifications, data flow diagrams, and operational procedures, to facilitate understanding, collaboration, and knowledge sharing across AI and analytics teams.

You will have proven experience as a Data Engineer, with a track record of designing and implementing complex data pipelines and infrastructure solutions that support advanced analytics and AI initiatives. You will possess expertise in data modeling, ETL (Extract, Transform, Load) processes, and data warehousing concepts, with proficiency in SQL and scripting languages.

The ideal candidate will have strong hands-on experience with big data technologies and frameworks, such as Hadoop, Spark, Kafka, and Flink, as well as cloud platforms commonly used for AI workloads. Familiarity with containerization and orchestration technologies, such as Docker and Kubernetes, and DevOps practices for CI/CD, including ML model deployment and data pipeline automation, is also essential.

You will have excellent analytical, problem-solving, and communication skills, with the ability to translate complex technical concepts into clear and actionable insights. Proven ability to work effectively in a fast-paced, collaborative environment, with a passion for innovation, continuous learning, and contributing to AI-driven solutions is required.

Unlock the Power of Data Engineering

Our team is seeking a highly analytical and detail-oriented data engineer to join our rapidly growing organization.

• Design and implement scalable and efficient architecture for data pipelines, ensuring seamless data flow across multiple endpoints.
• Deploy technical customizations to pre-packaged software solutions.
• Create and deploy micro-services and APIs to facilitate data transfer and integration between various systems.
• Perform data transformation activities, including data cleansing, data mining, and data processing, utilizing a variety of technologies and tools.

• Bachelor's degree in a relevant field (e.g., Computer Science, Data Science, Information Technology) or equivalent experience.
• 2+ years of experience in data engineering or a related role.
• Proficiency in data pipeline development, including ETL processes.
• Strong programming skills in languages such as Python, C#, or Java.
• Experience in extracting applicable data from databases using SQL.

Joining our organization at this phase of growth provides opportunity for accelerated career development working closely with our leadership team. Our solutions aren't just about solving today's challenges they're about setting the foundation for tomorrow's innovation and success.

We prioritize the goals of our clients, offering a fresh alternative to traditional consultancy approaches. No legacy-minded advice or pushy sales tactics just honest, results-driven solutions.

Why Join Us

• Client-First Philosophy: We prioritize the goals of our clients, offering a fresh alternative to traditional consultancy approaches.
• Technology Agnostic Excellence: We're not here to sell software. We help businesses maximize their existing technology investments and identify the most suitable new tools when necessary.
• Data-Driven Innovation: We enable businesses to turn accurate, accessible, and actionable data into real-time insights, driving tangible business results.
• Sustainable Client Growth: Our solutions aren't just about solving today's challenges they're about setting the foundation for tomorrow's innovation and success.

A visionary opportunity for a seasoned data professional to shape and drive organisational success.

• Promote a unified data strategy across multiple entities, leveraging advanced analytics and decision-making capabilities.
• Develop and implement robust governance frameworks to ensure data quality, integrity, and compliance with regulatory standards.
• Lead the design and implementation of scalable data platforms that support business growth and inform strategic decisions.
• Collaborate with stakeholders to identify opportunities for AI and machine learning adoption, driving actionable insights and business outcomes.
• Foster a culture of secure and responsible data sharing across internal and external partners, ensuring alignment with organisational values and goals.
• Provide expert guidance and training to develop high-performing teams of data professionals, promoting a data-driven approach to decision-making.

This challenging role offers a unique chance for an experienced leader to make a lasting impact on the organisation's data strategy and operations.

Our client is a leading player in the high-frequency trading space, setting new standards in crypto trading using innovative strategies and cutting-edge technology. Our team focuses on building a robust data infrastructure to support business-critical data pipelines.

You will be designing, maintaining, and optimizing our data backbone in Clickhouse, including cluster performance and schema tuning. This is a high-impact opportunity to work across the full data lifecycle, from ingestion to analytics, in close collaboration with Technology and Trading teams.

• Design and maintain robust data pipelines to support real-time and batch processing to support internal analytics and ML projects.
• Manage and optimize our Clickhouse data warehouse, including cluster performance and schema tuning.
• Collaborate with backend engineers, trading teams, and data stakeholders to ensure data quality, observability, and governance across critical pipelines.
• Support internal initiatives by building tooling and monitoring for business and technical metrics.
• Take ownership of scheduling and workflow orchestration (Argo, Airflow, etc.) and contribute to CI/CD automation.

• At least 5 years of professional experience in data engineering or backend infrastructure.
• Mastery in Python and SQL, especially in complex joins, window functions, and performance optimization.
• Hands-on experience with Clickhouse (especially the MergeTree engine family) or similar columnar DBs.
• Familiarity with workflow schedulers (e.g., Argo Workflows, Airflow, or Kubeflow) and Kafka architecture for streaming messages
• Comfortable with CI/CD pipelines (GitLab CI, ArgoCD, GitHub Actions).
• Experience with monitoring and BI tools such as Grafana for technical/business dashboards.

We are seeking a highly skilled Data Engineer to join our team. As a Data Engineer, you will be responsible for designing, implementing, and optimizing data pipelines and infrastructure to support our advanced analytics and AI initiatives.

Key Responsibilities:

• Design, develop, and maintain scalable and reliable data pipelines to ingest, transform, and load diverse datasets from various sources.
• Implement robust data integration processes to seamlessly integrate data from different sources, ensuring consistency, reliability, and data quality for analytics and AI use cases.
• Design and optimize data storage solutions, including relational databases, NoSQL databases, data lakes, and cloud storage services, to efficiently store and manage large volumes of data for AI and machine learning model consumption.
• Optimize data processing and query performance to enhance system scalability, reliability, and efficiency, leveraging techniques such as indexing, partitioning, caching, and parallel processing—especially for AI model training and inference pipelines.
• Implement data governance frameworks to ensure data security, privacy, integrity, and compliance with regulatory requirements, including data encryption, access controls, and auditing—crucial for responsible AI deployment.
• Monitor data pipelines and infrastructure components, proactively identify and address issues, and perform routine maintenance tasks to ensure system stability and reliability across AI and data science environments.

Requirements:

• Pipeline Development: Design, develop, and maintain scalable and reliable data pipelines to ingest, transform, and load diverse datasets from various sources, including structured and unstructured data, streaming data, and real-time feeds, with consideration for downstream AI/ML workloads.
• Data Integration: Implement robust data integration processes to seamlessly integrate data from different sources, ensuring consistency, reliability, and data quality for analytics and AI use cases.
• Data Storage: Design and optimize data storage solutions, including relational databases, NoSQL databases, data lakes, and cloud storage services, to efficiently store and manage large volumes of data for AI and machine learning model consumption.
• Performance Optimization: Optimize data processing and query performance to enhance system scalability, reliability, and efficiency, leveraging techniques such as indexing, partitioning, caching, and parallel processing—especially for AI model training and inference pipelines.
• Data Governance: Implement data governance frameworks to ensure data security, privacy, integrity, and compliance with regulatory requirements, including data encryption, access controls, and auditing—crucial for responsible AI deployment.
• Monitoring and Maintenance: Monitor data pipelines and infrastructure components, proactively identify and address issues, and perform routine maintenance tasks to ensure system stability and reliability across AI and data science environments.
• Collaboration: Collaborate closely with cross-functional teams, including data scientists, ML engineers, architects, and domain experts, to understand AI/ML requirements, gather insights, and deliver integrated, production-ready data solutions.
• Documentation: Create comprehensive documentation, including technical specifications, data flow diagrams, and operational procedures, to facilitate understanding, collaboration, and knowledge sharing across AI and analytics teams.
• Prior experience as a Data Engineer, with a track record of designing and implementing complex data pipelines and infrastructure solutions that support advanced analytics and AI initiatives.
• Expertise in data modeling, ETL (Extract, Transform, Load) processes, and data warehousing concepts, with proficiency in SQL and scripting languages (e.g., Python, Scala)—especially in AI pipeline preparation and feature engineering.
• Strong hands-on experience with big data technologies and frameworks, such as Hadoop, Spark, Kafka, and Flink, as well as cloud platforms (e.g., AWS, Azure, GCP) commonly used for AI workloads.
• Familiarity with containerization and orchestration technologies, such as Docker and Kubernetes, and DevOps practices for CI/CD (Continuous Integration/Continuous Deployment), including ML model deployment and data pipeline automation.
• Experience supporting AI/ML initiatives, including the preparation of training datasets, model input/output data flows, MLOps integration, and experimentation tracking.
• Excellent analytical, problem-solving, and communication skills, with the ability to translate complex technical concepts into clear and actionable insights.
• Proven ability to work effectively in a fast-paced, collaborative environment, with a passion for innovation, continuous learning, and contributing to AI-driven solutions.
  
  

Why Join Our Team?

• Make a meaningful impact on industries and society by working on cutting-edge AI and data engineering projects.
• Work with a diverse team of experts from various disciplines, fostering creativity, learning, and growth.
• Enjoy ample opportunities for professional development, career advancement, and leadership roles in a rapidly growing organization.
• Be part of a culture of curiosity, excellence, and collaboration, where your ideas are valued, and your contributions are recognized and rewarded.
  
  

This is a mid-senior level role that requires strong technical skills, business acumen, and excellent communication skills. If you are passionate about data engineering and AI, and thrive in a dynamic and collaborative environment, we encourage you to apply.

Join a world-class consulting firm to design and lead impactful data architectures that enable transformative business insights and drive innovation across industries. Are you driven to design scalable, secure, and efficient data architectures that empower organizations to make smarter decisions? We are looking for a seasoned Data Architect Manager to join a premier global consulting firm, leading the creation and optimization of sophisticated database systems for our clients. In this role, you will spearhead the development and management of data solutions that ensure data accessibility, high performance, and compliance with industry regulations. Your Impact
Project & Delivery Leadership

• Architect and deploy robust database solutions and data models tailored to business requirements.
• Analyze client workflows, applications, and programming needs to determine database architecture demands.
• Guarantee that database implementations comply with internal policies and external regulations.
• Manage the installation and configuration of data systems, ensuring seamless client operations.
• Develop detailed design documentation and architecture reports for leadership review.
• Lead data migration from legacy platforms to new database environments.
• Continuously monitor system performance, conduct diagnostics, troubleshoot issues, and integrate new features for improvement.
• Identify and recommend system enhancements to boost database efficiency and reliability.
• Deliver training and mentorship to team members to enhance their technical expertise.
• Provide prompt support and resolution for any database system challenges.

• Proven experience in data architecture, data science, or data analysis roles, with a strong track record of managing complex database architectures and data migrations.
• Proficient in statistical sampling, data mining, segmentation techniques, and advanced analytical methods to uncover key insights, trends, and relationships from complex data sets.
• Deep expertise in database design principles and hands-on experience with SQL and Oracle databases.
• Skilled in data visualization tools such as Tableau, D3.js, and R to communicate insights effectively.
• Exceptional organizational, analytical, and problem-solving abilities combined with strong communication skills to engage both technical and non-technical stakeholders.
• Solid understanding of regulatory compliance and best practices related to data systems and governance.
• Bachelor’s degree in Computer Science, Engineering, or a related field; advanced degrees and professional certifications are a plus.
• Minimum of 8 years of relevant experience in data architecture or closely related roles.
• Proven ability to collaborate effectively across multidisciplinary teams and engage senior leadership.
• We are specifically interested in professionals currently or previously with: McKinsey & Company, Boston Consulting Group (BCG), Bain & Company, Kearney, Strategy&, Oliver Wyman, Roland Berger, or Arthur D. Little.

Join a world-class consulting firm to design and lead impactful data architectures that enable transformative business insights and drive innovation across industries.
Are you driven to design scalable, secure, and efficient data architectures that empower organizations to make smarter decisions? We are looking for a seasoned Data Architect Manager to join a premier global consulting firm, leading the creation and optimization of sophisticated database systems for our clients.
In this role, you will spearhead the development and management of data solutions that ensure data accessibility, high performance, and compliance with industry regulations.
Your Impact
Project & Delivery Leadership

• Architect and deploy robust database solutions and data models tailored to business requirements.
• Analyze client workflows, applications, and programming needs to determine database architecture demands.
• Guarantee that database implementations comply with internal policies and external regulations.
• Manage the installation and configuration of data systems, ensuring seamless client operations.
• Develop detailed design documentation and architecture reports for leadership review.
• Lead data migration from legacy platforms to new database environments.
• Continuously monitor system performance, conduct diagnostics, troubleshoot issues, and integrate new features for improvement.
• Identify and recommend system enhancements to boost database efficiency and reliability.
• Deliver training and mentorship to team members to enhance their technical expertise.
• Provide prompt support and resolution for any database system challenges.

• Proven experience in data architecture, data science, or data analysis roles, with a strong track record of managing complex database architectures and data migrations.
• Proficient in statistical sampling, data mining, segmentation techniques, and advanced analytical methods to uncover key insights, trends, and relationships from complex data sets.
• Deep expertise in database design principles and hands-on experience with SQL and Oracle databases.
• Skilled in data visualization tools such as Tableau, D3.js, and R to communicate insights effectively.
• Exceptional organizational, analytical, and problem-solving abilities combined with strong communication skills to engage both technical and non-technical stakeholders.
• Solid understanding of regulatory compliance and best practices related to data systems and governance.
• Bachelor’s degree in Computer Science, Engineering, or a related field; advanced degrees and professional certifications are a plus.
• Minimum of 8 years of relevant experience in data architecture or closely related roles.
• Proven ability to collaborate effectively across multidisciplinary teams and engage senior leadership.
• We are specifically interested in professionals currently or previously with: McKinsey & Company, Boston Consulting Group (BCG), Bain & Company, Kearney, Strategy&, Oliver Wyman, Roland Berger, or Arthur D. Little.

We are seeking a skilled professional to fill the role of Data Engineer, responsible for building foundational components of an AI platform.

The ideal candidate will have expertise in data catalogue, ingestion, batch and streaming transformations, AI/ML enabled enrichment, storage layer and resilient pipelines.

Key responsibilities include contributing to the development of generic DataOps and MLOps components, implementing robust batch and streaming data processing and ML pipelines, extending core functionality with Data Governance, Data Quality and Policy Management best practices.

• Design and implement data pipelines using Spark, Flink, Beam, Clickhouse, Kafka, Temporal, Airflow or similar technologies.
• Collaborate with solution and product teams on POC projects, providing data engineering support and guidelines for platform usage.

A Bachelor's degree in Computer Science or related field and 7+ years of programming experience is required. Proficiency in SQL and either Python or Java is necessary, along with experience building OLAP solutions with Clickhouse and data visualization tools/frameworks.

A competitive remuneration package includes healthcare, education support, leave benefits and more.

An open, diverse and inclusive environment encourages personal growth and focuses on ground-breaking, industry-first innovations.

Outstanding learning, development & growth opportunities are available via structured training programs and innovative, high-tech projects.