ai engineer

data scientist

devops engineer

data engineer

operations engineer

cloud data engineer

Michael Page

Architect and scale data pipelines using Azure Data Factory, Synapse, and DatabricksBuild AI/ML pipelines that power investment insights and automation toolsEngineer seamless data flows from trading systems, market feeds, and financial platformsDesign smart data models for analytics, risk, and compliance reportingCollaborate with investment teams to turn data into strategic advantageDrive performance, security, and cost-efficiency across cloud data systemsChampion data governance with robust documentation and access controls

AI Data Engineer

Client of Michael Page

<div> <div> <ul> <li> </li></ul></div></div><div><div><div> </div> </div> </div> <div> Job Description <div> <div> <ul> <li>Architect and scale data pipelines using Azure Data Factory, Synapse, and Databricks</li> <li>Build AI/ML pipelines that power investment insights and automation tools</li> <li>Engineer seamless data flows from trading systems, market feeds, and financial platforms</li> <li>Design smart data models for analytics, risk, and compliance reporting</li> <li>Collaborate with investment teams to turn data into strategic advantage</li> <li>Drive performance, security, and cost-efficiency across cloud data systems</li> <li>Champion data governance with robust documentation and access controls</li> </ul> </div> </div> </div> <div> The Successful Applicant <div> <div> <ul> <li>Strong expertise in Azure data services and Power BI</li> <li>Hands-on experience with LLMs and Generative AI (OpenAI, LLaMA)</li> <li>Skilled in RAG pipelines and vector databases (e.g. FAISS, Pinecone)</li> <li>Proficient in Python, SQL, and familiar with PySpark or Scala</li> <li>Experience with CI/CD and orchestration tools for data workflows</li> <li>Exposure to investment platforms like Bloomberg, FactSet, or Aladdin.</li> </ul> </div> </div> </div> <div> </div><div> </div>

Whiteshield

<div>Whiteshield is a global policy advisory and AI economics firm known for our ability to respond to global challenges rapidly and incisively. We use the most advanced tools and technology and combine them with our team of leading international experts to engage decision-makers in tackling society's most significant challenges. We are recognized for our rapid decision support, innovation, data science algorithms and deep policy expertise. We are specialists in &quot;connecting the dots&quot; between policy, business and technology.
Whiteshield X is Whiteshield&rsquo;s product business, hosting our PaaS and SaaS product offering. Partnered with Google Cloud, we bring advanced solutions to governments around the world to drastically improve citizen outcomes in areas such as employment, trade, and education. We develop a host of different SaaS modules from job matching to managing scholarship programs, and from delivering financial support to growth support for SMEs. These modules support governments around the world with delivering G2C and G2B services efficiently and significantly improve policy outcomes.
We are seeking a Senior Data Engineer who combines deep technical expertise with architectural vision to build the next generation of AI-accelerated data platforms.
You will play a pivotal role in defining and implementing the organization&rsquo;s data architecture and platform strategy &mdash; ensuring that data is reliable, well-structured, and easily consumable across systems and applications. This is both a strategic and hands-on position: you&rsquo;ll design scalable architectures, build data pipelines, and collaborate with application and product teams to embed data excellence into every part of the technology stack.
If you&rsquo;re passionate about data craftsmanship, AI-driven automation, and modern cloud-native ecosystems, this is an opportunity to make a large-scale impact.
What You'll Do<ul><li>
Data Architecture &amp; Strategy</li></ul><ul><li>
Define and maintain the enterprise data architecture blueprint, spanning ingestion, lake, warehouse, and semantic layers.</li></ul><ul><li>
Collaborate closely with application and platform teams to design robust data strategies &mdash; ensuring alignment between application design, API contracts, and long-term data scalability.</li></ul><ul><li>
Develop integration patterns and governance models that support cross-platform interoperability, data lineage, and secure data sharing.</li></ul><ul><li>
Partner with cloud architects to ensure performance, scalability, and compliance across Azure environments.</li></ul><ul><li>
Data Engineering &amp; Orchestration</li></ul><ul><li>
Build and optimize end-to-end data pipelines using Apache Airflow, Azure Fabric, Azure Data Factory, and SSIS &mdash; integrating diverse data sources (transactional, streaming, and analytical).</li></ul><ul><li>
Implement AI-accelerated data processing for intelligent schema mapping, deduplication, and performance optimization.</li></ul><ul><li>
Develop and maintain ETL/ELT frameworks using SQL and Python (Pandas, PySpark) for high-volume, low-latency data movement.</li></ul><ul><li>
Data Modeling &amp; Warehousing</li></ul><ul><li>
Design semantic data models, dimensional schemas, and data marts using SSAS, PostgreSQL, MSSQL, and Azure Synapse/Fabric.</li></ul><ul><li>
Collaborate with BI and analytics teams to support dashboards, reports, and forecasting tools with clean, contextualized, and well-documented data models.</li></ul><ul><li>
Performance, Quality &amp; Governance</li></ul><ul><li>
Define standards for data quality, lineage, observability, and access control.</li></ul><ul><li>
Implement automated validation, monitoring, and reconciliation mechanisms.</li></ul><ul><li>
Work with governance and security teams to ensure compliance with national and organizational data frameworks.</li></ul><ul><li>
Collaboration &amp; Enablement</li></ul><ul><li>
Partner with application engineers, data scientists, and business analysts to deliver AI-ready, high-quality data products.</li></ul><ul><li>
Act as a bridge between application development and data architecture, ensuring consistent data design across services.</li></ul><ul><li>
Mentor junior data engineers and champion best practices in modern data engineering and DevOps for data.</li></ul>
Requirements
Qualifications<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Engineering, or a related discipline.</li></ul><ul><li>
6+ years of experience in data engineering and architecture, preferably in complex or government-scale environments.</li></ul>
Expertise in:<ul><li>
Orchestration: Apache Airflow, Azure Data Factory, or equivalent.</li></ul><ul><li>
ETL / BI Stack: SSIS, SSAS, dbt, Power BI semantic models.</li></ul><ul><li>
Databases: MSSQL, PostgreSQL, Azure Synapse, Azure Fabric Data Lake.</li></ul><ul><li>
Cloud Platforms: Deep knowledge of Azure (Fabric, Synapse, Blob, Data Lake, Functions, Logic Apps). Google Cloud is a plus.</li></ul><ul><li>
Languages: SQL and Python (Pandas, PySpark); experience with CI/CD pipelines and GitOps practices.</li></ul><ul><li>
Demonstrated experience designing AI-ready architectures and leveraging machine learning for data enrichment and automation.</li></ul><ul><li>
Strong understanding of data governance, interoperability standards, and scalable architecture design patterns.</li></ul>
Benefits
WHY CHOOSE US |
Our Commitment to Equal Opportunities: At Whiteshield, we are committed to providing equal opportunities in employment regardless of individual characteristics. We recognize that our employees feel appreciated when their thoughts and values are respected and considered. We&rsquo;re committed to maintaining and driving an inclusive culture and workplace where all talents are nurtured and feel empowered to contribute.
Celebrating Achievements: At Whiteshield, we seek to reward those who demonstrate exceptional individual achievements above and beyond expectations in the pursuit of continuously seeking excellence for our clients. When individuals excel, we show our appreciation and celebrate achievements by generously recognizing and supporting the career progression of those who make unique contributions to the firm.
Empowering Our People: At Whiteshield, we recognize that our employees are the core to our success and believe that when our exceptional talent comes together, and wellbeing is a priority &ndash; innovation thrives. We are dedicated to promoting and encouraging a healthy work-life balance and adopting a genuinely flexible working model to empower our employees to pursue a balance that suits their personal needs.</div>

Senior Data Engineer - AI-Accelerated Data Architecture & Platforms

Antons

Key Responsibilities 
<ul>
<li>
 Architect &amp; Design: Lead the design and implementation of Data Lakehouse architectures, including batch and real-time streaming pipelines using Delta Lake.
</li>
<li>
 Cloud Data Platforms: Build and optimize scalable data engineering solutions leveraging Azure Data Factory, Databricks, ADLS, Azure Event Hub, PySpark/Scala/SQL.
</li>
<li>
 Data Governance &amp; Cataloging: Drive the adoption and implementation of Unity Catalog, ensuring robust data lineage, governance, schema, and access control mechanisms.
</li>
<li>
 Performance &amp; Cost Optimization: Review solutions and guide teams on performance tuning, cloud cost optimization, and architectural best practices.
</li>
<li>
 Technical Leadership: Act as a trusted advisor to engineering teams, providing hands-on guidance in data engineering, analytics, and cloud-native design patterns.
</li>
<li>
 Innovation &amp; Strategy: Evaluate new tools, frameworks, and approaches to continuously improve the enterprise data ecosystem.
</li>
</ul>

Solution Architect

Talabat

Job Details Location: United Arab Emirates Location: Dubai Industry: Information Technology (IT) Function: Software Engineering / Development Gender: Any Candidate Nationality: Any Candidate Preferred Location: Any Job Type: Full-time What You ll Do * Develop and maintain scalable data pipelines for batch and streaming use cases * Work with Apache Kafka for real-time ingestion and event-driven architectures * Use GCP and AWS tools such as BigQuery, Dataflow, S3, and Lambda for storage and processing * Orchestrate workflows using Airflow or equivalent scheduling tools * Ensure data quality and reliability with monitoring, alerting, and validation systems * Collaborate with data scientists, analysts, and product teams to deliver data solutions * Optimize systems for both cost efficiency and performance across cloud platforms * Participate in code reviews, documentation, and technical knowledge sharing Candidate Requirements * 1 3 years of experience in data engineering, software engineering, or related field * Proficiency in SQL and at least one programming language (Python preferred) * Understanding of ETL/ELT processes and data modeling concepts * Familiarity with cloud-based data warehouses and streaming tools such as Kafka * Experience working with GCP, AWS, or Azure environments * Strong communication skills for technical and non-technical collaboration * Growth mindset with eagerness to learn and take on new challenges Nice to Have * Knowledge of infrastructure-as-code tools like Terraform or CloudFormation * Experience with Docker or Kubernetes * Familiarity with data governance, security, and compliance practices

Data Engineer

Bayut.com

You will have the opportunity to build and work with both batch and real-time data processing pipelines. While working in a modern cloud-based data warehousing environment alongside a team of diverse, intense and interesting co-workers, you will liaise with other teams such as product &amp; tech, the core business verticals, trust &amp; safety, finance and others to enable them to be successful.
In this role, you will:
<ul>
 <li>Raw data integrations with primary and third-party systems</li>
 <li>Data warehouse modelling for operational and application data layers</li>
 <li>Development in Amazon Redshift cluster</li>
 <li>SQL development as part of agile team workflow</li>
 <li>ETL design and implementation in Matillion ETL</li>
 <li>Real-time data pipelines and applications using serverless and managed AWS services such as Lambda, Kinesis, API Gateway, etc.</li>
 <li>Design and implementation of data products enabling data-driven features or business solutions</li>
 <li>Data quality, system stability and security</li>
 <li>Coding standards in SQL, Python, ETL design</li>
 <li>Building data dashboards and advanced visualisations in Periscope Data with a focus on UX, simplicity and usability</li>
 <li>Working with other departments on data products i.e. product &amp; technology, marketing &amp; growth, finance, core business, advertising and others</li>
 <li>Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data</li>
 <li>Be able to work autonomously without supervision on complex projects</li>
 <li>Participate in the early morning ETL status check rotabr&gt;</li>
</ul>

Huspy

The Main Event: What You ll Drive, Build, and Own
Design and Scale Data Pipelines: Build and maintain reliable batch and streaming pipelines that connect our applications, events, and external sources to Snowflake, ensuring data flows seamlessly across our platform.
Streaming Data at Scale: Work with Kafka, Schema Registry, and event-driven architectures to power real-time data products and ensure downstream systems get trustworthy, well-structured events.
Pipeline Orchestration: Use Airflow to orchestrate complex workflows, automate dependencies, and ensure data availability for analytics and business processes.
Data Infrastructure &amp; Cloud Services: Leverage AWS tools (ECR, ECS, S3, etc.) to build scalable, containerized data services and optimize storage, compute, and costs.
Data Quality &amp; Observability: Implement testing frameworks, monitoring, and alerting for data pipelines to ensure reliability and trust at scale.
Infrastructure as Code: Manage data infrastructure with tools like Terraform, Helmfile, or CloudFormation, automating deployments and ensuring reproducibility.
Optimize for Scale and Performance: Continuously improve the throughput, latency, and cost efficiency of pipelines, ensuring the platform scales with the business.
Modeling &amp; Governance: Apply strong data modeling fundamentals (e.g., Kimball, Data Vault) and enforce governance around PII, compliance, and lifecycle management.
Collaboration for Impact: Partner with analysts, business stakeholders, and product teams to translate requirements into well-designed pipelines and models that unlock business value.
Automation &amp; CI/CD: Implement testing, linting, and automated deployments for data pipelines to ensure high-quality, production-ready code.

Explore 5347+ Cloud data engineer in Dubai this November. Find roles across top companies and apply now to boost your career.

5347 cloud data engineer jobs IN Dubai

AI Data Engineer

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Senior Data Engineer - AI-Accelerated Data Architecture & Platforms

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