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big data engineer

Mind Stream

<p>We are seeking a highly skilled <b>Azure Data Engineer</b> with extensive experience in building, optimizing, and managing scalable data solutions on Microsoft Azure. The ideal candidate will have hands-on expertise in <b>Azure Databricks, Data Factory, Data Lake Storage</b>, and <b>Event Hub</b>, along with strong programming and data engineering skills.</p><p>Required Skills and Qualifications:</p><ul><li>8+ years of experience as an Azure Data Engineer or similar role.</li><li>Strong expertise in Azure Databricks, Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), and Event Hub.</li><li>Proficiency in programming languages such as PySpark, Scala, or SQL.</li><li>Experience with data modeling, data warehousing, and big data technologies.</li><li>Knowledge of Delta Lake and other data storage formats.</li><li>Familiarity with data integration tools and techniques.</li><li>Excellent problem-solving skills and attention to detail.</li><li>Knowledge of data governance and data quality best practices.</li><li>Strong communication and collaboration skills.</li><li>Certification in Microsoft Azure Data Engineering or irelated areas is a plus</li><li>Bachelor&rsquo;s degree in Computer Science, Information Technology, or a related field.</li></ul><p>Job Type: Full-time</p><p>Application Question(s):</p><ul><li>Do you have a minimum of 8 years of total experience as a Data Engineer or in a similar role?</li><li>How many years of hands-on experience do you have with Azure Databricks?</li><li>How many years of experience do you have working with Azure Data Factory (ADF) and Azure Data Lake Storage (ADLS)?</li><li>Do you have experience with data modeling, data warehousing, and big data technologies?</li><li>What is your current and expected salary?</li><li>What is your notice period?</li></ul>

Azure Data Engineer

Dataiku

<div> <p>Dataiku s SaaS, cloud or on-premise deployed platform connects many Data Science technologies. Our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll  work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here. </p> <p>As a Field Engineer, you ll work with customers at every stage of their relationship with Dataiku - from the initial evaluations to enterprise-wide deployments. In this role, you will help customers to design, build, validate, and run their Data Science and AI Platforms.</p> <p>This role requires strong technical abilities, adaptability, inventiveness, and strong communication skills. Sometimes you will work with clients on traditional big data technologies such as SQL data warehouses, while at other times you will be helping them to discover and implement the most cutting edge tools; Spark on Kubernetes, cloud-based elastic compute engines, and GPUs. If you are interested in staying at the bleeding edge of big data and AI while maintaining a strong working knowledge of existing enterprise systems, this will be a great fit for you.</p> <ul> <li>Understand customer requirements in terms of scalability, availability and security and provide architecture recommendations</li> <li>Deploy Dataiku in a large variety of technical environments (SaaS, Kubernetes, Spark, Cloud or on-prem)</li> <li>Automate operation, installation, and monitoring of the Data Science ecosystem components in our infrastructure stack</li> <li>Collaborate with Revenue and Customer teams to deliver a consistent experience to our customers</li> <li>Drive technical success by being a trusted advisor to our customers and our internal account teams </li> </ul> </div>

Field Engineer

EMIRATES GLOBAL ALUMINIUM (EGA)

<ul><li><strong>Big Data Infrastructure:</strong> Design build, and maintain high-performance, cloud-based, fault-tolerant, scalable distributed Data infrastructure that supports the company’s data-intensive applications Real time/Batch/LLM’s. This includes developing strategies for data storage TBs, processing, and analysis, and implementing high-performance, scalable data pipelines for ML models and data products, supporting up to 50-60 use cases a year and thousands of IoT devices.</li><li>Create infrastructure as Code, perform configuration and set up managed data services. Build and deploy a data science playground for research and prototyping for the professional and citizen data science program being rolled out and supporting 15-20 citizen data scientists/ambassadors.</li><li><strong>Machine Learning Operations MLOps </strong> Develop and manage the ML operational process, working closely with the data science team to implement ML models into production, including edge. This includes streamlining the ML lifecycle, from model development and testing to deployment and implementing the monitoring and alerting strategy.</li><li><strong>Automation and Scalability:</strong> Implement automation tools and frameworks to manage system updates/changes. Ensure that all systems and infrastructures can scale effectively with the increase in IoT sensors and devices.</li><li><strong>Continuous Integration and Deployment CI CD:</strong> Oversee continuous integration and continuous deployment practices for the data and ML pipeline, ensuring that software can be reliably released at any time.</li><li><strong>System Monitoring and Reliability:</strong> Monitor system performance and reliability to ensure high levels of performance, availability, and security This includes identifying and fixing potential and existing system issues. Collaboration and Communication  Strong collaboration with Data Architect/Engineer, data scientists for the implementation and testing of new data services to provide an elastic data infrastructure.</li><li><strong>Security:</strong> Oversee and ensure that all Big Data and ML Ops platforms comply with the companies security standards and policies.</li><li><strong>Mentorship and Leadership:</strong> Act as a mentor to junior data members, providing guidance and support in their professional development. Promote a culture of performance, collaboration, and continuous learning within the data team.</li><li><strong>Innovation and Continuous Improvement:</strong> Stay up to date with industry trends and new technologies. Continuously explore innovative solutions and enhancements to the existing data architecture to improve its scalability, reliability, and efficiency.</li><li><strong>Problem Solving:</strong> Anticipate and resolve technical issues before they become roadblocks, maintaining the continuity of data flow and ensuring the highest levels of data quality and integrity.</li></ul><p><strong>AUTHORITY/DECISION MAKING:</strong></p><ul><li><strong>Infrastructure Design:</strong> Decide on the most effective design and implementation of the companys Big Data infrastructure.</li><li><strong>ML Ops Process:</strong> Make key decisions on the ML operational process, ensuring that ML models can be effectively integrated into production.</li><li><strong>Automation Tools:</strong> Choose the most appropriate automation tools and frameworks for the company&#x27;s needs.</li><li><strong>CI/CD Practices:</strong> Determine the best practices for continuous integration and deployment in the context of the company&#x27;s operations.</li><li><strong>System Monitoring:</strong> Make decisions on system monitoring strategies, including the selection of tools and responses to system performance metrics.</li><li><strong>Security Policies:</strong> Have a say in the implementation of security policies as they pertain to the Big Data and ML Ops platforms.</li><li><strong>Budget and Costing:</strong> Taking ownership of managing data platform costs and relevant data services.</li></ul>

Lead Data Ops Engineer

Bayut.com

<p>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.</p>
<p><strong>In this role, you will:</strong></p>
<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>

Data Engineer

Legacy Smart Employment Services

<p>- Architect and manage robust big data pipelines using the Hadoop ecosystem (HDFS, Hive, Pig, HBase, Sqoop, Flume, etc.)<br/>- Develop and optimize solutions using Spark, MapReduce, and NoSQL databases like Cassandra and HBase.<br/>- Write clean, scalable code in Java, Python, Scala, or R — bonus points if you&#x27;re comfortable in Linux environments.<br/>- Own end-to-end data engineering deliverables and lead the charge on performance, scalability, and reliability.<br/>- Collaborate with cross-functional teams to solve complex data and system integration challenges.</p>

Senior Data Engineer

Client of Michael Page

<div> <div> <ul> <li><br></li></ul></div></div><div><div><div> </div> </div> </div> <div><b> Job Description </b><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><b> The Successful Applicant </b><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><br></div><div> </div>

AI Data Engineer

Michael Page

<p>Architect and scale data pipelines using Azure Data Factory, Synapse, and Databricks</p><p>Build AI/ML pipelines that power investment insights and automation tools</p><p>Engineer seamless data flows from trading systems, market feeds, and financial platforms</p><p>Design smart data models for analytics, risk, and compliance reporting</p><p>Collaborate with investment teams to turn data into strategic advantage</p><p>Drive performance, security, and cost-efficiency across cloud data systems</p><p>Champion data governance with robust documentation and access controls</p>

Explore 5252+ Big data engineer in Dubai United Arab Emirates this November. Find roles across top companies and apply now to boost your career.

5252 big data engineer jobs IN Dubai United Arab Emirates

Azure Data Engineer

Field Engineer

Lead Data Ops Engineer

Data Engineer

Senior Data Engineer

AI Data Engineer

AI Data Engineer