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Manpower Middle East

<div>
 
 
 About the role:
 
 
 
 We are seeking an experienced data engineer to join our team building a scalable and secure health data platform. In this role, you will design, build and optimise data pipelines (batch &amp; streaming) for big data systems. Extracting, Analysing and Modelling of rich &amp; diverse health data sets.
 
 
 
 
 
 
 Responsibilities:
 
 
 
 Design and implement data pipelines, ETL processes, schemas, and data models to ingest, process, and prepare multi-petabyte scale datasets for downstream analytics and machine learning.
 
 
 Build and optimize data processing systems on modern platforms like Azure Fabric/Databricks, Spark, Delta Lake, Azure Data Factory/Airflow, Purview, Kafka, etc.
 
 
 Implement data quality, validation, and monitoring measures leveraging tools such as Great Expectations.
 
 
 Ensure compliance with security, access control, and regulatory requirements related to PHI and other sensitive data types.
 
 
 Support adoption of emerging standards like FHIR for healthcare data exchange.
 
 
 Collaborate with data scientists, analysts, and engineers to understand data needs and deliver performant, reliable data products
 
 
 Keep track of emerging technologies &amp; trends in the Data Engineering world, incorporating modern tooling and best practices.
 
 
 
 
 
 
 Qualifications:
 
 
 
 4+ years experience building and operating production big data platforms and pipelines
 
 
 Strong experience with SQL, Spark, workflow orchestrators(ADF/Airflow), distributed message bus, Python, Delta Lake, apache big data tool suites, Docker, Kubernetes, MPP
 
 
 Hands on with the design and implementation of cloud-based data solutions using platforms like Azure, AWS, or GCP, optimizing for scalability, cost-efficiency, and performance.
 
 
 Implement and maintain data lakes including data modeling, ETL processes, and data quality assurance to empower data-driven decisionmaking.
 
 
 Develop real-time data pipelines using streaming technologies like Apache Kafka or AWS Event hub, enabling timely insights and actions from incoming data streams.
 
 
 Previous experience of working on health data and Azure cloud is a strong plus
 
 
 Experience with Databricks or MS Fabric
 
 
 Strong track record of designing and implementing scalable data models, schemas, ETL logic
 
 
 Experience with data governance, master data management, data pseudonimization and anonymization, and data catalog solutions .
 
 
 A strong interest in learning new things and team player ethics.
 
 
 Strong analytical skills and good understanding of data structures and algorithms.
 
 
 Some exposure to Nextflow and or Nextflow Tower
 
 
 
 
 
 
 Nice to have:
 
 
 
 Experience building data pipelines for machine learning and working with unstructured datasets.
 
 
 Knowledge of genomics, medical imaging, and/or EHR data domains
 
 
 Knowledge of HIPAA, HL7 and other healthcare data privacy requirements.
 
 
 Azure Batch &amp; Blob Storage
 
</div>

Data Engineer

Converge

<div>
 
 
 Data Engineer | Abu Dhabi, UAE
 
 
 
 
 
 
 
 What This Role Is About
 
 
 
 Our client is looking for a Data Engineer, based in Abu Dhabi, to design, build, and optimise data pipelines and infrastructure that support business intelligence and analytics initiatives.
 
 
 
 
 
 This role will focus on managing large datasets, ensuring data accuracy and availability, and enabling efficient data flow across systems.
 
 
 
 
 
 You will work closely with cross-functional teams to support data-driven decision-making and improve overall data architecture.
 
 
 
 
 
 You will also play a key role in maintaining data quality, enhancing data models, and supporting advanced analytics use cases.
 
 
 
 
 
 
 The Client&rsquo;s Definition of the Ideal Fit
 
 
 <ul>
 <li>
 7+ years of experience in data engineering or a related field.
 </li>
 <li>
 Bachelor&rsquo;s degree in Coastal Engineering, Marine Engineering, or a related discipline.
 </li>
 <li>
 Strong experience in building and managing data pipelines and data infrastructure.
 </li>
 <li>
 Proficiency in data tools, databases, and ETL processes.
 </li>
 <li>
 Strong understanding of data modelling, data warehousing, and data governance.
 </li>
 <li>
 Ability to work with cross-functional teams and support data-driven initiatives.
 </li>
 </ul>
 
 
 
 
 This is an opportunity to work on impactful data projects while leveraging domain expertise within a specialised environment in Abu Dhabi.
 
</div>

Khazna Data Centers

<div>
 
 
 Khazna was founded in 2012 and has grown rapidly into becoming the leading and trusted wholesale Data Center provider in the Middle East and North Africa region. Through our Data Centers, we provide industry benchmark levels of power supply and cooling services to better serve the growing need for data center operations in the UAE and wider region.
 
 
 
 
 
 
 We are seeking a
 
 Data Engineer
 
 to join our
 
 Command &amp; Control Center &ndash; Data Analytics &amp; Reporting
 
 team, reporting to the
 
 Manager, Data &amp; BI
 
 . This centralized role is responsible for designing, developing, and maintaining scalable data pipelines that support analytics, reporting, and AI/ML initiatives for data center operations. The Data Engineer will ensure data integrity, optimize data architecture, and manage ETL (Extract, Transform, Load) processes across cloud and on-premises platforms to enable effective, data-driven decision-making.
 
 
 
 
 
 
 Key Accountabilities:
 
 
 
 
 
 <ul>
 <li>
 Support the development of scalable data warehouses, lakes and resilient data pipelines to support high-velocity data processing in a wholesale data center environment
 </li>
 <li>
 Design and implement Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes to clean, normalize and transform data from diverse sources, including Internet of Things (IoT) sensors, Building Management System (BMS) within data center operations
 </li>
 <li>
 Automate data ingestion, transformation and storage workflows for real-time analytics, ensuring low-latency insights for operational decision-making across data center environments
 </li>
 <li>
 Set up streaming data services to enable continuous migration of critical data center infrastructure metrics into analytics platforms for real-time monitoring
 </li>
 <li>
 Work with Integration teams, Data Warehouse engineers and Analytics teams to build highly optimized, resilient and scalable data center data processing architectures
 </li>
 <li>
 Define data sourcing strategies, tagging mechanisms and aggregation methods to ensure seamless availability of structured and unstructured data for data center analytics
 </li>
 <li>
 Collaborate with Data Scientists and Business Intelligence (BI) teams to enable AI/ML model development, predictive analytics and operational intelligence for data center operations
 </li>
 <li>
 Develop calculation methodologies for statistical computation of KPIs related to Power Usage Effectiveness (PUE), Water Usage Effectiveness (WUE), uptime and asset utilization in data centers
 </li>
 <li>
 Identify critical data points and sources that drive KPI computations and aggregate site-level metrics for centralized data center performance reporting
 </li>
 <li>
 Build reporting source files for dashboards, enabling executive leadership to monitor data center performance trends across regional and site-level operations
 </li>
 <li>
 Generate historical trend analyses, benchmarking individual data center site performance against portfolio-wide averages to drive efficiency improvements
 </li>
 <li>
 Conduct Exploratory Data Analysis (EDA) to identify patterns, anomalies and correlations that impact energy efficiency, workload distribution and infrastructure health in data centers
 </li>
 <li>
 Gather required historical and real-time data from internal platforms and external sources, ensuring comprehensive datasets for advanced analytics in data center environments
 </li>
 <li>
 Develop simulations and scenario models to analyse potential business impacts, optimize data center capacity planning and mitigate operational risks
 </li>
 <li>
 Update models and forecasting frameworks based on market trends, data center infrastructure expansion plans and internal priority shifts
 </li>
 <li>
 Research and implement cutting-edge data engineering techniques, contributing to industry-leading best practices in large-scale data center data infrastructure management
 </li>
 <li>
 Deliver data archiving, backup and disaster recovery strategies, ensuring high availability and business continuity for critical data center data assets
 </li>
 <li>
 Ensure seamless integration of data platforms with enterprise applications, enabling end-to-end visibility and automated decision-making across the data center ecosystem
 </li>
 </ul>
 
 
 
 
 
 Minimum Qualifications:
 
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or master&rsquo;s degree in computer science (or) related to Data Engineering
 </li>
 <li>
 Certifications in cloud data platforms preferred
 </li>
 <li>
 4+ years of experience in data engineering, ETL development or database management
 </li>
 <li>
 Strong proficiency in SQL, Python or Scala
 </li>
 <li>
 Experience with cloud data platforms (AWS, Azure, GCP)
 </li>
 <li>
 Hands-on experience with data pipeline tools like Apache Airflow, Kafka or Spark
 </li>
 <li>
 Understanding of data modeling, warehousing and governance principles
 </li>
 </ul>
 
 
 
 
 
 Additional skills:
 
 
 
 
 
 <ul>
 <li>
 Ability to troubleshoot complex data challenges, optimize pipeline performance and drive continuous improvements in large-scale infrastructure
 </li>
 <li>
 Strong ability to work across Data Science, Engineering, IT and Business Intelligence teams to align data solutions with business needs
 </li>
 <li>
 Expertise in translating technical data models and engineering concepts into clear insights for non-technical stakeholders
 </li>
 </ul>
 
 
 
 
 
 Training/Certifications Preferred:
 
 
 
 
 
 <ul>
 <li>
 AWS Certified Data Analytics &ndash; Specialty
 </li>
 <li>
 Google Professional Data Engineer
 </li>
 <li>
 Microsoft Certified: Azure Data Engineer Associate
 </li>
 <li>
 Apache Spark Developer Certification
 </li>
 </ul>
 
 
</div>

ai71

<div>
 
 About AI71:
 
 
 
 AI71 is an industry leader in artificial intelligence, delivering innovative solutions that empower developers, businesses and governments to solve complex challenges. AI71 builds secure, enterprise-ready applications powered by cutting-edge technology&mdash;tailored for knowledge workers and sector-specific needs. AI71 bridges the gap between advanced AI and real-world impact. Guided by a strong commitment to research and responsibility, we create transformative solutions that drive progress and empower communities.
 
 
 
 The Role:
 
 
 
 As a Senior Data Engineer, you will be responsible for designing, developing, and maintaining advanced, scalable data systems that power critical business decisions. You will lead the development of robust data pipelines, ensure data quality and governance, and collaborate across cross-functional teams to deliver high-performance data platforms in production environments. This role requires a deep understanding of modern data engineering practices, real-time processing, and cloud-native solutions.
 
 
 
 What You'll Do:
 
 
 
 <ul>
 <li>
 Data Pipeline Development &amp; Management:
 </li>
 <ul>
 <li>
 Design, implement, and maintain scalable and reliable data pipelines to ingest, transform, and load structured, unstructured, and real-time data feeds from diverse sources.
 </li>
 <li>
 Manage data pipelines for analytics and operational use, ensuring data integrity, timeliness, and accuracy across systems.
 </li>
 <li>
 Implement data quality tools and validation frameworks within transformation pipelines.
 </li>
 </ul>
 <li>
 Data Processing &amp; Optimization:
 </li>
 <ul>
 <li>
 Build efficient, high-performance systems by leveraging techniques like data denormalization, partitioning, caching, and parallel processing.
 </li>
 <li>
 Develop stream-processing applications using Apache Kafka and optimize performance for large-scale datasets.
 </li>
 <li>
 Enable data enrichment and correlation across primary, secondary, and tertiary sources.
 </li>
 </ul>
 <li>
 Cloud, Infrastructure, and Platform Engineering:
 </li>
 <ul>
 <li>
 Develop and deploy data workflows on AWS or GCP, using services such as S3, Redshift, Pub/Sub, or BigQuery.
 </li>
 <li>
 Containerize data processing tasks using Docker, orchestrate with Kubernetes, and ensure production-grade deployment.
 </li>
 <li>
 Collaborate with platform teams to ensure scalability, resilience, and observability of data pipelines.
 </li>
 </ul>
 <li>
 Database Engineering:
 </li>
 <ul>
 <li>
 Write and optimize complex SQL queries on relational (Redshift, PostgreSQL) and NoSQL (MongoDB) databases.
 </li>
 <li>
 Work with ELK stack (Elasticsearch, Logstash, Kibana) for search, logging, and real-time analytics.
 </li>
 <li>
 Support Lakehouse architectures and hybrid data storage models for unified access and processing.
 </li>
 </ul>
 <li>
 Data Governance &amp; Stewardship:
 </li>
 <ul>
 <li>
 Implement robust data governance, access control, and stewardship policies aligned with compliance and security best practices.
 </li>
 <li>
 Establish metadata management, data lineage, and auditability across pipelines and environments.
 </li>
 </ul>
 <li>
 Machine Learning &amp; Advanced Analytics Enablement:
 </li>
 <ul>
 <li>
 Collaborate with data scientists to prepare and serve features for ML models.
 </li>
 <li>
 Maintain awareness of ML pipeline integration and ensure data readiness for experimentation and deployment.
 </li>
 </ul>
 <li>
 Documentation &amp; Continuous Improvement:
 </li>
 <ul>
 <li>
 Maintain thorough documentation including technical specifications, data flow diagrams, and operational procedures.
 </li>
 <li>
 Continuously evaluate and improve the data engineering stack by adopting new technologies and automation strategies
 
 </li>
 </ul>
 </ul>
 
 What You'll Bring:
 
 
 
 <ul>
 <li>
 8+ years of experience in data engineering within a production environment.
 </li>
 <li>
 Advanced knowledge of Python and Linux shell scripting for data manipulation and automation.
 </li>
 <li>
 Strong expertise in SQL/NoSQL databases such as PostgreSQL and MongoDB.
 </li>
 <li>
 Experience building stream processing systems using Apache Kafka.
 </li>
 <li>
 Proficiency with Docker and Kubernetes in deploying containerized data workflows.
 </li>
 <li>
 Good understanding of cloud services (AWS or Azure).
 </li>
 <li>
 Hands-on experience with ELK stack (Elasticsearch, Logstash, Kibana) for scalable search and logging.
 </li>
 <li>
 Familiarity with AI models supporting data management.
 </li>
 <li>
 Experience working with Lakehouse systems, data denormalization, and data labeling practices.
 </li>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, Data Science, or a related field.
 </li>
 <li>
 Demonstrated success in designing, scaling, and operating data systems in cloud-native and distributed environments.
 </li>
 <li>
 Proven ability to work collaboratively with cross-functional teams including product managers, data scientists, and DevOps.
 
 
 </li>
 </ul>
 
 Great Pluses / Preferred Experience
 
 
 
 <ul>
 <li>
 Working knowledge of data quality tools, lineage tracking, and data observability solutions.
 </li>
 <li>
 Experience in data correlation, enrichment from external sources, and managing data integrity at scale.
 </li>
 <li>
 Understanding of data governance frameworks and enterprise compliance protocols.
 </li>
 <li>
 Exposure to CI/CD pipelines for data deployments and infrastructure-as-code.
 
 
 </li>
 </ul>
 
 Why AI71:
 
 
 
 <ul>
 <li>
 Mission-Driven Work: Work on cutting-edge AI applications with a talented and passionate team, solving real-world challenges in critical sectors.
 </li>
 <li>
 Unparalleled Opportunity: This is a chance to innovate and solve real-world challenges using AI at a company with unique access to world-leading models and resources.
 </li>
 <li>
 Career Growth: We offer competitive compensation, benefits, and significant career growth opportunities as a foundational member of the team.
 </li>
 <li>
 World-Class Environment: Enjoy a flexible working environment and the latest tools &amp; technologies needed to do your best work.
 </li>
 </ul>
</div>

Dubai Holding

<div>
 
 Established in 2004, Dubai Holding is a global investment company with investments in more than 34 countries and a combined workforce of nearly 45,000 individuals. In line with the vision of Dubai&rsquo;s leadership and economic diversification strategy, Dubai Holding companies have nurtured sectors, irrevocably transforming Dubai&rsquo;s socio-economic landscape and positioning Dubai as a diversified, globally integrated economy.
 
 
 
 
 
 Dubai Holding is committed to the diversification of Dubai&rsquo;s non-oil economy. Our portfolio, valued at over AED 280+ billion, spans 10 sectors, including real estate, hospitality, leisure &amp; entertainment, ICT, design, education, media, retail, manufacturing &amp; logistics, and science.
 
 
 
 
 
 
 For the Good of Tomorrow
 
 
 
 Dubai Holding is looking to hire a
 
 Data Engineer
 
 . The role is responsible for leading the design, development, and maintenance of data solutions that support product teams in leveraging data for their specific needs. This role involves building and managing data pipelines, data lakes, and data warehouses, ensuring high-quality data delivery, and fostering a culture of process and data quality within development teams while being compliant with data protection/ privacy regulations and policies.
 
 
 
 
 
 If you are ready to embark on a dynamic journey where your talents are valued, and your contributions make a real impact, we would like to hear from you.
 
 
 
 
 
 
 Key Accountabilities:
 
 
 
 
 Data Infrastructure &amp; Pipeline Development
 
 
 <ul>
 <li>
 Design, build, and maintain data pipelines, lakes, and warehouses.
 </li>
 <li>
 Develop ETL jobs and stored procedures/functions/packages.
 </li>
 <li>
 Ensure robust data storage and high-quality data delivery.
 </li>
 </ul>
 
 
 Technical Guidance &amp; Integration
 
 
 <ul>
 <li>
 Own and implement ETL operating standards.
 </li>
 <li>
 Provide guidance on infrastructure for analytics and AI use cases.
 </li>
 <li>
 Collaborate with backend developers and IT architecture teams for seamless integration.
 </li>
 </ul>
 
 
 Product &amp; Stakeholder Collaboration
 
 
 <ul>
 <li>
 Work with Product Owners to understand and meet data needs.
 </li>
 <li>
 Translate product requirements into engineering plans and roadmaps.
 </li>
 <li>
 Gather stakeholder requirements and build architectures aligned with business goals.
 </li>
 </ul>
 
 
 Quality &amp; Process Excellence
 
 
 <ul>
 <li>
 Promote a culture of process and data quality.
 </li>
 <li>
 Implement best practices for data management and quality assurance.
 </li>
 <li>
 Support bug fixing and performance optimization.
 </li>
 </ul>
 
 
 Agile Delivery &amp; Team Collaboration
 
 
 <ul>
 <li>
 Advocate for agile methodologies and iterative development
 </li>
 <li>
 Collaborate cross-functionally to deliver project outcomes.
 </li>
 </ul>
 
 
 
 
 
 Who we are looking for:
 
 
 <ul>
 <li>
 At least 3-6 years of experience in Data Engineering roles
 </li>
 <li>
 Bachelor&rsquo;s Degree in a quantitative field (Mathematics, Engineering, Statistics, Science, Data Science/ AI); Advanced degrees preferred.
 </li>
 <li>
 Experience in Big Data platform like Databricks, Spark, Hive, Palantir Foundry etc.
 </li>
 <li>
 Experience in implementing AI solutions including OCR, Large Language Models, etc.
 </li>
 <li>
 Experienced with data modelling, design patterns, building highly scalable and secured analytical solutions.
 </li>
 <li>
 Proficiency in Python, SQL, PL/SQL, Spark and similar languages
 </li>
 <li>
 Strong analytical and problem-solving skills
 </li>
 <li>
 Experience working in a tech/ product environment is a plus
 </li>
 </ul>
 
 
 
 
 
 Behavioural Competencies
 
 
 <ul>
 <li>
 High-energy, ownership-driven mindset
 </li>
 <li>
 Strong problem-solving and analytical skills
 </li>
 <li>
 Excellent communication and collaboration abilities
 </li>
 <li>
 Comfortable navigating ambiguity and driving clarity
 </li>
 <li>
 Experience in agile/start-up environments preferred
 </li>
 <li>
 Successful track record of leading complex projects is a plus
 </li>
 </ul>
 
 
 
 
 
 As much as we would be delighted to entertain all applicants, due to the high volumes of applications, only successful applicants will be contacted within 14 business days.
 
 
 
 
 
 
 
 This job description is not all inclusive. Dubai Holding reserves the right to amend this job description at any time. Dubai Holding is an Equal Opportunity Employer, committed to a diverse and inclusive work environment.
 
 
</div>

YO IT CONSULTING

<div>Job Title: Data Engineer
Job Type: Contractor
Location: Remote
Job Summary:
We are seeking an expert Data Engineer to join our customer&rsquo;s team and play a pivotal role in developing next-generation AI agents. In this fully remote role, you will leverage your strong data engineering, coding, and AI/ML expertise to help train and optimize advanced AI systems. Collaborate with talented professionals in a dynamic environment where your technical skills and innovative mindset will directly impact the project's success.
Key Responsibilities:
<div><ul><li>Design, implement, and manage data pipelines to support complex AI agent training initiatives.</li></ul>
<ul><li>Collaborate closely with AI/ML engineers to ensure efficient data flows and high-quality training datasets.</li></ul>
<ul><li>Develop and maintain scalable ETL processes using Python, MySQL, and PostgreSQL.</li></ul>
<ul><li>Utilize JAVA and JavaScript to integrate diverse data sources and enable seamless data exchange.</li></ul>
<ul><li>Contribute to the optimization of AI models through effective data engineering practices.</li></ul>
<ul><li>Document data processes comprehensively and communicate technical concepts clearly to both technical and non-technical stakeholders.</li></ul>
<ul><li>Troubleshoot and resolve data issues, ensuring data integrity and reliability for AI applications.</li></ul>
</div>Required Skills and Qualifications:
<div><ul><li>Bachelor&rsquo;s degree in Computer Science, Engineering, or a related field.</li></ul>
<ul><li>3+ years of hands-on experience as a Data Engineer, with proven expertise in AI/ML projects.</li></ul>
<ul><li>Advanced proficiency in Python, MySQL, PostgreSQL, JAVA, and JavaScript.</li></ul>
<ul><li>Strong understanding of AI concepts and experience in training AI agents.</li></ul>
<ul><li>Exceptional written and verbal communication skills, with a focus on clarity and collaboration.</li></ul>
<ul><li>Experience implementing robust data pipelines and scalable architecture for machine learning projects.</li></ul>
<ul><li>Self-motivated, detail-oriented, and able to thrive in a fully remote team environment.</li></ul>
</div>Preferred Qualifications:
<div><ul><li>Master&rsquo;s degree in a related field.</li></ul>
<ul><li>Direct experience with AI agent frameworks and real-world deployment projects.</li></ul>
<ul><li>Previous work in fast-paced startup or innovation-driven environments.</li></ul></div></div>

Data Engineer - Remote

Explore 1956+ Data engineer in United Arab Emirates this May. Find roles across top companies and apply now to boost your career.

1956 data engineer jobs In United Arab Emirates

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer - Remote

Data Engineer - Remote