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COZMALABS

We are looking for an experienced&#8239; Data Engineer&#8239;to join our team full-time. This role requires a strong background in building and optimizing data pipelines, with a focus on supporting AI-driven solutions. The candidate will work closely with software engineers to ensure reliable data flows for AI models and contribute to cloud-based data integration using Microsoft Azure.Key Responsibilities:<ul><li>Design, develop, and maintain scalable data pipelines and ETL processes to support AI-driven projects</li><li>Build and optimize data infrastructure to ensure efficient data management, processing, and storage in cloud environments (Azure)</li><li>Collaborate with AI engineers to facilitate data preparation for machine learning models and AI solutions</li><li>Ensure data pipelines are secure, reliable, and meet performance standards</li><li>Monitor and troubleshoot data pipeline performance to ensure timely and accurate data delivery</li><li>Implement data governance policies and ensure compliance with data security standards</li></ul>Required Qualifications:<ul><li>Proven experience as a Data Engineer, with a focus on building and maintaining complex data pipelines for AI projects</li><li>Proficiency in SQL and experience with relational databases (e.g., PostgreSQL, SQL Server) and NoSQL databases (e.g., MongoDB)</li><li>Expertise in cloud-based data solutions, specifically Microsoft Azure (e.g., Azure Data Factory, Azure Synapse, Azure Databricks)</li><li>Experience with data integration tools and ETL frameworks (e.g., Apache Airflow)</li><li>Proficiency in at least one programming language for data manipulation (e.g., Python)</li><li>Knowledge of data warehousing solutions and best practices</li><li>Experience in working with data pipelines for AI or machine learning workflows</li><li>Strong problem-solving and analytical skills</li><li>Bachelor&rsquo;s degree in Computer Science, Engineering, or a related field</li><li>Proficiency in English (written and spoken)</li></ul>Desirable Qualifications:<ul><li>Familiarity with machine learning models and data preprocessing for AI solutions</li><li>Knowledge of containerization tools (Docker, Kubernetes) for data pipeline deployments</li></ul>Job Type: Full-time

Data Engineer

Mindstream

Role: Azure Data EngineerLocation: QatarDuration: 1 Year and extendableSalary: Best in marketExperience: 8+ YearsEducation: Bachelor&rsquo;s degree in Computer Science, Information Technology, or a related field.&middot; Strong expertise in Azure Databricks, Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), and Event Hub&middot; Proficiency in programming languages such as PySpark, Scala, or SQL.&middot; Experience with data modeling, data warehousing, and big data technologies.&middot; Knowledge of Delta Lake and other data storage formats.&middot; Familiarity with data integration tools and techniques.&middot; Excellent problem-solving skills and attention to detail.&middot; Knowledge of data governance and data quality best practices.&middot; Strong communication and collaboration skills.&middot; Certification in Microsoft Azure Data Engineering or related areas is a plusForward resume to careers@mind-stream.netWhatsApp 974 30107270Job Type: Permanent

Azure Data Engineer

Codvo.ai

<div><div><div>Job Description:Data Engineer (OT Data) (Category - Engineer)
Sector: Oil and Gas
Location: Doha, Qatar<div>
Experience - 10 years</div><div></div> 
About Us
At Codvo, we are committed to building scalable, future-ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting-edge technology. 
The Opportunity:
The Data Engineer will be a foundational architect of our delivery strategy, responsible for building and maintaining the data ecosystem required for our scoped-out use cases. You will be the crucial link between our vast, complex data sources and our advanced analytics ambitions. This involves tackling the unique challenges of the oil and gas sector, bridging the worlds of operational technology (OT)&mdash;with its real-time drilling data, SCADA systems, and seismic surveys&mdash;and information technology (IT). Your mission is to build the specific, high-performance data pipelines required to deliver our portfolio of projects. This means going beyond simple data movement; you will be creating reliable, scalable, and secure data products that serve as the fuel for our most critical AI models and analytics dashboards, directly enabling tangible business value and competitive advantage.<div></div> 
Key Responsibilities:<ul><li>Architect &amp; Build Data Pipelines: Design, construct, install, test, and maintain highly scalable data management systems and ETL/ELT pipelines.</li><li>Integrate Diverse Data Sources: Develop processes to ingest and integrate high-volume, high-velocity data from SCADA systems, historians (like OSIsoft PI, Aspen InfoPlus.21), DCS, PLC, and IoT sensors.</li><li>Cloud Data Platform Development: Implement and manage data solutions on the Microsoft Azure cloud platform, Leveraging services like Azure IoT Hub, Azure Event Hubs, and Azure Stream Analytics for real-time ingestion and processing of operational technology (OT) data.</li><li>Data Modelling &amp; Warehousing: Design and implement data models optimized for time-series data from industrial assets, supporting operational dashboards and real-time analytics.</li><li>Enable Advanced AI: Build the data infrastructure to support AI/ML models for predictive maintenance, operational anomaly detection, and process optimization using real-time OT data.</li><li>Champion Master Data Management (MDM): Design and implement MDM strategies and solutions to create a single, authoritative source of truth for critical data domains such as wells, equipment, and assets, ensuring data consistency across the enterprise.</li><li>Ensure Data Quality &amp; Governance: Implement robust data quality checks, validation rules, and monitoring to ensure the accuracy, consistency, and reliability of our data. Adhere to and help shape our data governance policies.</li><li>Embrace Industry Standards: Champion and implement industry-specific data standards and models, such as the OSDU&trade; Data Platform, to ensure interoperability and a unified data view across the upstream lifecycle.</li><li>Collaborate &amp; Innovate: Work closely with a cross-functional team of geoscientists, drilling engineers, data scientists, and business analysts to understand their data needs and deliver effective solutions.</li><li>Automate &amp; Optimize: Identify opportunities for process automation and infrastructure optimization to improve data delivery, scalability, and cost-effectiveness.</li><li>Security First: Implement and maintain security best practices to protect our sensitive and proprietary data assets.</li></ul> 
Required Skills and Qualifications:<ul><li>Bachelor's in engineering, Information Systems, or a related quantitative field.</li><li>5+ years of proven experience in a data engineering role.</li><li>Experience within oil and gas industry is highly preferred.</li><li>Demonstrable experience building and operationalizing large-scale data pipelines and applications.</li></ul> 
Technical Proficiencies:<ul><li> 
Expert-level proficiency in SQL and Python for data manipulation and pipeline development.</li><li>Big Data Technologies: Hands-on experience with distributed computing frameworks like Apache Spark (PySpark). Experience with streaming technologies like Kafka is a plus.</li><li>Cloud Platforms: Deep experience with Microsoft Azure (Azure Data Lake Storage, Azure Data Factory, Azure Databricks, Azure Synapse).</li><li>Data Warehousing/Lakehouse: Proven experience with modern data platforms Databricks Delta Lake.</li><li>AI &amp; ML Knowledge: Understanding of machine learning lifecycles and the data requirements for training and deploying AI/ML models.</li><li>Orchestration: Experience with workflow orchestration tools like Airflow, Dagster, or Azure Data Factory.</li><li>Databases: Strong understanding of both relational (e.g., PostgreSQL, SQL Server) and NoSQL databases. Experience with graph databases (e.g., Neo4j) and vector databases is highly desirable.</li><li>Version Control: Proficiency with Git and CI/CD best practices.</li></ul> 
Preferred Qualifications:<ul><li>Familiarity with historian systems (e.g., OSIsoft PI System) and their data structures.</li><li>Hands-on experience with the OSDU&trade; Data Platform.</li><li>Experience working with industrial communication protocols (e.g., OPC UA, Modbus TCP/IP).</li><li>Understanding of cybersecurity considerations for OT environments and data segregation.</li><li>Experience integrating data from ERP systems like SAP.</li><li>Professional certifications in Azure or Databricks.</li><li>Advanced SQL skills, including query optimization and performance tuning.</li><li>Knowledge of containerization technologies (Docker, Kubernetes).</li><li>Experience of constructing and maintaining enterprise knowledge graphs.</li></ul> 
Domain - Oil &amp; Gas
Location - Doha, Qatar</div></div></div>

Data Engineer Lead (OT Data)

Sight Spectrum

Key Responsibilities:<ul><li>Design and manage secure hybrid network architectures (on-prem &amp; multi-cloud).</li><li>Configure routing, switching (BGP, OSPF), firewalls (Palo Alto, Fortinet, Cisco ASA), VPNs, and load balancers (F5, Azure Application Gateway).</li><li>Implement WAFs, zero trust policies, and ensure compliance (ISO 27001, NIA Qatar).</li><li>Secure cloud connectivity using ExpressRoute, NSGs, Private Endpoints, and hybrid VPNs.</li><li>Integrate network telemetry with SIEM/SOAR tools (Azure Sentinel, Chronicle, Splunk).</li><li>Support incident response, threat detection, and continuous risk assessment.</li><li>Collaborate with Cloud, DevOps, and Security teams to embed security-by-design.</li></ul>Required Skills &amp; Experience:<ul><li>10+ years in network &amp; infrastructure security (enterprise scale).</li><li>Strong in routing/switching, firewalls, VPN, WAF, load balancing, and zero trust.</li><li>Hands-on with Azure &amp; GCP cloud security, Terraform, Ansible, and IaC tools.</li><li>Certifications preferred: CISSP, CCSP, AZ-500, SC-100, or GCP Security Engineer.</li><li>Experience in Oil &amp; Gas, Energy, or Critical Infrastructure sectors preferred.</li></ul>Job Type: Contract Contract length: 12 months

Senior Data Engineer

Proven experience with Azure DevOps and implementing CI/CD pipelines.<ul><li>Strong knowledge of Azure data services, specifically Azure Databricks and Azure Data Factory.</li><li>Proficiency in Databricks Asset Bundle for Databricks Ci/CD.</li><li>Experience with scripting and automation tools (e.g., PowerShell, Python).</li><li>Experience in implementing selective deployment for ADF data pipelines.</li><li>Understanding of containerization and orchestration tools (e.g., Docker, Kubernetes) is a plus.</li><li>Excellent problem-solving skills and ability to troubleshoot complex CI/CD issues.</li><li>Strong communication skills and ability to collaborate effectively with cross-functional teams.</li><li>Knowledge of security best practices for CI/CD pipelines and Azure environments.</li><li>Detail-oriented with a focus on delivering high-quality, reliable automation solutions.</li><li>Bachelor's degree in Computer Science, Information Technology, or related field.</li><li>Minimum of 5 years of experience in DevOps or related roles.</li></ul>Job Type: Full-timeApplication Question(s):<ul><li>How many years of experience do you have working with Azure DevOps?</li><li>Do you have hands-on experience in implementing CI/CD pipelines for Azure data projects?</li><li>Have you worked with Azure Databricks and Azure Data Factory (ADF)?</li><li>Are you familiar with Databricks Asset Bundle for Databricks CI/CD?</li><li>How many years of experience do you have with Python or PowerShell scripting?</li><li>Have you implemented selective deployment for ADF pipelines?</li><li>What is your current and expected salary?</li><li>What is your notice period or earliest joining availability?</li></ul>

Azure DevOps (Data) Engineer

Advanced Artificial Mind

AI Solutions Engineer / Data Scientist / Machine Learning EngineerLocation: Qatar Department: ITResponsibilities:<ul><li>Develop and deploy custom AI models &mdash; particularly in Arabic NLP, document classification, and chatbots.</li><li>Work on data preprocessing, training, and fine-tuning large language models.</li><li>Build APIs or applications integrating AI capabilities into client systems.</li><li>Collaborate with cross-functional teams to define problem statements and evaluate solutions.</li></ul>Requirements:<ul><li>Experience with Python, TensorFlow / PyTorch, Hugging Face, or similar frameworks.</li><li>Familiarity with n8n workflows.</li><li>Knowledge of Arabic language processing and text analytics.</li><li>Strong problem-solving and research skills.</li><li>Familiarity with deploying AI models in cloud environments (Azure, AWS, GCP).</li></ul>Job Type: Full-time

AI Solutions Engineer / Data Scientist / Machine Learning Engineer

Shift Group

<div>
 
 
 Role Overview:
 
 The Data Analyst will be at the forefront of data strategy and monetization, responsible for turning data into growth insights that drive business decisions, optimize performance, and unlock new revenue streams.
 
 
 This role blends analytical depth, business intelligence, data engineering, and strategic thinking, ideal for professionals passionate about using data to fuel digital growth and audience value.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 Data Analytics &amp; Insights
 
 
 <ul>
 <li>
 Collect, clean, and analyze data from multiple digital sources (web, app, CRM, marketing, and sales systems).
 </li>
 <li>
 Build automated dashboards and reports using tools like Power BI, Tableau, or Google Data Studio to track platform KPIs.
 </li>
 <li>
 Identify user trends, engagement drivers, and conversion patterns across verticals (classifieds, content, properties, jobs, cars, etc.).
 </li>
 <li>
 Generate actionable insights that support leadership decision-making and operational efficiency.
 </li>
 <li>
 Analyze marketing funnel performance and user acquisition metrics to identify growth opportunities.
 </li>
 </ul>
 
 
 
 
 
 Data Engineering &amp; ETL
 
 
 <ul>
 <li>
 Design, build, and maintain robust and scalable ETL pipelines to ingest and process data from a wide variety of sources, including web, app, CRM, marketing, analytics logs, and sales systems.
 </li>
 <li>
 Utilize both off-the-shelf and custom solutions (e.g., Azure Data Factory, custom Python scripts) to collect, transform, clean, and load data into our data warehouse, ensuring data quality, integrity, and accessibility.
 </li>
 <li>
 Develop a consolidated data architecture to support unified reporting, business intelligence, and advanced analytics.
 </li>
 </ul>
 
 
 
 
 
 Machine Learning &amp; Predictive Modeling
 
 
 <ul>
 <li>
 Design, develop, and deploy machine learning and predictive models to understand customer behavior, predict churn, and identify growth opportunities.
 </li>
 <li>
 Apply statistical analysis and modeling techniques to build frameworks for measuring user lifetime value, optimizing pricing strategies, and forecasting revenue.
 </li>
 <li>
 Implement A/B testing frameworks and conduct experiments to measure the performance of new features, marketing campaigns, and product changes.
 </li>
 </ul>
 
 
 
 
 
 Customer Data Platform (CDP) &amp; Analytics
 
 
 <ul>
 <li>
 Lead the development and implementation of a Customer Data Platform (CDP) to create a single, unified view of the customer journey.
 </li>
 <li>
 Integrate the CDP with our marketing and sales platforms to enable advanced audience segmentation, personalization, and targeted advertising.
 </li>
 <li>
 Attach machine learning models to the CDP to analyze customer behavior patterns, predict future actions, and deliver actionable insights to the business.
 </li>
 </ul>
 
 
 
 
 
 Monetization &amp; Growth
 
 
 <ul>
 <li>
 Develop data-driven monetization strategies, such as audience segmentation, advertising optimization, and data-based product offerings.
 </li>
 <li>
 Partner with Sales and Marketing teams to enhance campaign targeting, ad performance (CTR, CPC, CPM, ROAS), and audience segmentation, and cross-channel attribution
 </li>
 <li>
 Support pricing strategy and revenue forecasting through predictive analytics and business modeling.
 </li>
 <li>
 Build frameworks to measure subscription and user lifetime value.
 </li>
 </ul>
 
 
 
 
 
 Data Infrastructure &amp; Governance
 
 
 <ul>
 <li>
 Collaborate with Technology teams to ensure accuracy, integrity, and consistency of data across all systems.
 </li>
 <li>
 Establish and maintain clear KPIs, data definitions, and governance standards.
 </li>
 <li>
 Ensure compliance with ethical and legal standards for data usage.
 </li>
 </ul>
 
 
 
 
 
 Cross-Functional Collaboration
 
 
 <ul>
 <li>
 Work with Marketing, Product, and Commercial teams to drive experiments (A/B tests) and measure performance outcomes.
 </li>
 <li>
 Present findings in a visually engaging and business-focused manner for executives and stakeholders.
 </li>
 <li>
 Translate analytical insights into actionable business recommendations.
 </li>
 </ul>
 
 
 
 
 
 Qualifications &amp; Experience
 
 
 
 
 
 <ul>
 <li>
 
 Education:
 
 Bachelor's or Master's degree in Data Science, Business Analytics, Statistics, Computer Science, Economics, or related field.
 </li>
 <li>
 
 Experience:
 
 5&ndash;8 years of experience in data analytics, business intelligence, data engineering, or growth analytics within a digital, e-commerce, or media technology company.
 </li>
 <li>
 
 Technical Skills:
 
 </li>
 <li>
 Strong knowledge of SQL, Python (pandas, numpy, matplotlib, scikit-learn), and BI tools such as Power BI, Tableau, or Google Data Studio.
 </li>
 <li>
 Experience with ETL/ELT tools (e.g., Azure Data Factory, Apache Airflow, or similar).
 </li>
 <li>
 Proficiency in machine learning and predictive modeling techniques for forecasting, customer behavior analysis, and LTV modeling.
 </li>
 <li>
 Experience with data warehousing solutions (e.g., Snowflake, BigQuery, Azure Synapse).
 </li>
 <li>
 Knowledge of Customer Data Platforms (CDP) and customer journey analytics.
 </li>
 <li>
 Experience with Google Analytics 4, BigQuery, or Looker is a plus.
 </li>
 <li>
 
 Business Skills:
 
 Proven track record in using data to enhance business performance, customer acquisition, retention, and monetization.
 </li>
 <li>
 
 Soft Skills:
 
 Strong communication, data storytelling, and cross-functional collaboration. Ability to translate complex data into simple insights.
 </li>
 </ul>
 
 
 
 
 
 Preferred
 
 
 <ul>
 <li>
 Experience in audience segmentation, ad performance analytics, or subscription data modeling.
 </li>
 <li>
 Background in digital media, advertising, or marketplace platforms.
 </li>
 <li>
 Familiarity with data monetization models and creation of data-based products or reports.
 </li>
 <li>
 Hands-on experience implementing CDP solutions (e.g., Segment, mParticle, Adobe CDP, or similar platforms).
 </li>
 <li>
 Experience with cloud platforms (Azure, or GCP) for data infrastructure.
 </li>
 <li>
 Knowledge of A/B testing methodologies and experimentation platforms.
 </li>
 </ul>
</div>

Data Analyst – Business Intelligence

Explore 1092+ Data engineer in Doha this November. Find roles across top companies and apply now to boost your career.