data analyst

data engineer

senior data engineer

data scientist

devops engineer

cloud data engineer

ATOM Insurance

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Job description<br></b></p><div>
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 <p>You will be working on projects with teams from across our ATOM Platform and Business Intelligence/Data Science practice. Reporting to the Chief Product Officer, you will deliver digestible, contemporary and immediate data content to support and drive business decisions. The key focus of the role is to deliver reports, dashboards and custom solutions for various business critical requirements. You will be involved in all aspects of data engineering from delivery planning, estimating and analysis, all the way through to data architecture and pipeline design, delivery and production implementation. From day one, you will be involved in the design and implementation of complex data solutions ranging from batch to streaming and event-driven architectures, across cloud, on-premise and hybrid client technology landscapes.</p> <p> <strong>As a Data Engineer, you will:</strong> </p> <p>Build different types of data warehousing layers based on specific use cases</p> <p>Lead the design, implementation, and successful delivery of large-scale, critical, or difficult data solutions involving a significant amount of work</p> <p>Build scalable data infrastructure and understand distributed systems concepts from a data storage and compute perspective</p> <p>Utilize expertise in SQL and have a strong understanding of ETL and data modeling</p> <p>Ensure the accuracy and availability of data to customers and understand how technical decisions can impact their business s analytics and reporting</p> <p>Be proficient in at least one scripting/programming language to handle large volume data processing</p> <p> <strong> <em>We are looking for 5+ years of experience in data engineering in a customer or business facing capacity.</em> </strong> </p>
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Knowledge and Skills<br></p><div>
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 <p> <strong>To be considered for this role you will have:</strong> </p> <p>Ability to understand and articulate requirements to technical and non-technical audiences</p> <p>Stakeholder management and communication skills, including prioritising, problem solving and interpersonal relationship building</p> <p>Strong experience in SDLC delivery, including waterfall, hybrid and Agile methodologies. Experience delivering in an agile environment</p> <p>Experience of implementing and delivering data solutions and pipelines on AWS Cloud Platform</p> <p>A strong understanding of data modelling, data structures, databases, and ETL processes</p> <p>An in-depth understanding of large-scale data sets, including both structured and unstructured data</p> <p>Strong SQL and Python knowledge</p> <p>Knowledge and experience of delivering CI/CD and DevOps capabilities in a data environment</p> <p> <strong>Basic qualifications:</strong> </p> <p>At least 3- 5 years of Consulting or client service delivery experience on Amazon AWS (AWS)</p> <p>At least 3- 5 years of experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases, NoSQL and data warehouse solutions</p> <p>Extensive experience providing practical direction within the AWS Native and Hadoop</p> <p>Experience with private and public cloud architectures, pros/cons, and migration considerations</p> <p>Minimum of 5 years of hands-on experience in AWS and Big Data technologies such as Java, Node.js, C##, Python, SQL, EC2, S3, Lambda, Spark/SparkSQL, Hive/MR, Pig, Oozie and streaming technologies such as Kafka, Kinesis, NiFI etc.</p> <p>3-5+ years of hands on experience in programming languages such as Java, c#, node.js, python, pyspark, spark, SQL, Unix shell/Perl scripting etc.</p> <p>Experience working with DevOps tools such as GitLabs, Jenkins, CodeBuild, CoePipeline CodeDeploy, etc.</p> <p>Bachelors or higher degree in Computer Science or a related discipline</p> <p> <strong>Must have at least one AWS certification:</strong> </p> <p>Certified AWS Developer   Associate</p> <p>Certified AWS DevOps   Professional</p> <p>Certified AWS Big Data Specialty</p> <p> <strong>Nice-to-have skills/qualifications:</strong> </p> <p>DevOps on an AWS platform. Multi-cloud experience a plus</p> <p>Experience developing and deploying ETL solutions on AWS using tools like Talend, Informatica, Matillion</p> <p>Strong in Java, C##, Spark, PySpark, Unix shell/Perl scripting</p> <p>IoT, event-driven, microservices, containers/Kubernetes in the cloud</p>
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Data Engineer

Whiteshield

<div><p>We are seeking an experienced Senior Data Engineer to lead the design, development, and optimization of large-scale data platforms across Azure, Google Cloud, and hybrid environments.</p><p>
You will architect data pipelines that power AI-driven analytics, knowledge graphs, and agentic automation across enterprise and national-level projects.</p><p></p><p>
The ideal candidate combines deep expertise in data architecture, orchestration, and cloud infrastructure with hands-on experience using AI-assisted development tools to accelerate delivery and ensure scalability, reliability, and intelligence in every layer of the data stack.</p><p></p><p>
Key Responsibilities</p><p></p><p>
Architect and lead the design of end-to-end data pipelines using Apache Airflow, Azure Data Factory, and Google Cloud Composer.</p><p></p><p>
Design and manage data lake, data warehouse, and OLAP architectures using MSSQL, SSIS, and SSAS.</p><p></p><p>
Build and optimize ETL/ELT frameworks integrating structured, semi-structured, and unstructured data across APIs, databases, and streaming platforms.</p><p></p><p>
Implement and maintain graph and NoSQL databases (e.g., Neo4j, Cosmos DB, MongoDB, Elasticsearch) to support semantic analytics, search, and recommendation systems.</p><p></p><p>
Establish standards for data quality, lineage, governance, and observability.</p><p></p><p>
Collaborate with AI engineers, data scientists, and business analysts to enable retrieval-augmented generation (RAG), knowledge graph, and agentic orchestration use cases.</p><p></p><p>
Drive multi-cloud infrastructure automation through Terraform, Pulumi, or Bicep and CI/CD pipelines.</p><p></p><p>
Champion AI-assisted coding practices (e.g., GitHub Copilot, ChatGPT, Cursor) to enhance productivity, testing, and documentation.</p><p></p><p>
Mentor junior engineers, review designs, and promote best practices in data architecture, DevOps, and AI-native engineering.</p><p></p><p>
Contribute to strategic roadmap planning, including capacity scaling, cost optimization, and data-driven innovation initiatives.</p><p><b>
Requirements</b></p><ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Engineering, or related field.</li><li>
<b>5&ndash;10 years </b>of progressive experience in data engineering, data architecture, or analytics infrastructure roles.</li><li>
Deep expertise in SQL/T-SQL, performance optimization, and data modeling.</li><li>
Proven hands-on experience with SSIS and SSAS, including cube design and deployment.</li><li>
Advanced proficiency with Airflow (custom DAGs, operators, sensors, and monitoring).</li><li>
Solid understanding of Azure (Data Factory, Synapse, Blob Storage, Functions) and Google Cloud (BigQuery, Cloud Storage, Pub/Sub) ecosystems.</li><li>
Strong Python development skills for ETL, automation, and API integration.</li><li>
Experience with Docker, Kubernetes, and CI/CD workflows for data services.</li><li>
Hands-on experience with graph databases (Neo4j, Neptune, TigerGraph) and NoSQL stores (MongoDB, Cosmos DB, Elasticsearch, etc.).</li><li>
Demonstrated use of AI-powered development tools (GitHub Copilot, ChatGPT, Replit Ghostwriter, Code Interpreter) in professional workflows.</li><li>
Knowledge of data security, governance, and compliance frameworks (GDPR, ISO 27001, NIST)</li></ul><p></p><p><b>
Benefits</b></p><p></p><p><b>
Our Commitment to Equal Opportunities:</b> 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.</p><p><b>
Celebrating Achievements:</b> 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.</p><p><b>
Empowering Our People:</b> 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.</p></div>

Senior Technology 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>
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 <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>
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VaporVM

<div><div><div><b>Date Posted:</b></div>
20 October, 2025</div>
<div><div><b>Industry:</b></div>
IT Services and IT Consulting</div>
<div><div><b>Location:</b></div>
VAPORVM IT SERVICES DMCC</div></div>
<br><div><h2 class="jobSectionHeader"><b>Job Description:</b></h2>
<div><h3 class="jobSectionHeader"><b>Role Overview:</b></h3>
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We are seeking <b>one to two experienced Snowflake Data Engineers</b> to join our team in Riyadh. The ideal candidates will have a strong grasp of <b>Snowflake architecture, data warehousing, and workflow automation</b>, with hands-on experience in <b>big data and cloud integration</b>.</p>
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Key Responsibilities:</b></h3>
<ul><li>Design, develop, and optimize data pipelines and transformations within <b>Snowflake</b>.
</li><li>Work with <b>Virtual Warehouses, Snowpipe, Streams, and Tasks</b> to manage data workflows.
</li><li>Implement <b>data models</b> and ensure performance tuning and query optimization.
</li><li>Automate workflows using <b>Apache Airflow</b> or <b>Luigi</b>.
</li><li>Integrate Snowflake with <b>GCP</b> and other big data tools like <b>Apache Spark, Hadoop, and Kafka</b>.
</li></ul><h3 class="jobSectionHeader"><b>Requirements:</b></h3>
<ul><li>Proven experience working with <b>Snowflake architecture and SQL</b>.
</li><li>Strong understanding of <b>data warehouse concepts and modeling</b>.
</li><li>Familiarity with <b>GCP</b> and workflow automation tools.
</li><li>Experience with <b>big data ecosystems</b> (Spark, Hadoop, Kafka).</li></ul></div></div><p></p>

SnowFlake 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

Washmen

<div><div><b>Position Overview</b></div><div>
We're seeking a self-sufficient Senior Data Engineer to build and scale our data infrastructure supporting product, engineering and analytics team. You'll architect data pipelines, optimize our data platform, and ensure the teams have reliable, high-quality data to drive business decisions.</div><div>
This is a hands-on role for someone who can own the entire data engineering stack - from ingestion to transformation to orchestration. You'll work independently to solve complex data challenges and build scalable solutions.</div><div></div><div><b><br>
Core Responsibilities</b></div><div></div><div><b><br>
Data Pipeline Development &amp; Optimization</b></div><div>
Design, build, and maintain scalable data pipelines using Spark and Databricks</div><div>
Develop ETL/ELT workflows to process large volumes of customer behavior data</div><div>
Optimize Spark jobs for performance, cost efficiency, and reliability</div><div>
Build real-time and batch data processing solutions</div><div>
Implement data quality checks and monitoring throughout pipelines</div><div>
Ensure data freshness and SLA compliance for analytics workloads</div><div></div><div><b><br>
AWS Data Infrastructure</b></div><div>
Architect and manage data infrastructure on AWS (S3, Glue, EMR, Redshift)</div><div>
Design and implement data lake architecture with proper partitioning and optimization</div><div>
Configure and optimize AWS Glue for ETL jobs and data cataloging</div><div>
Shifting Glue jobs to Zero ETL</div><div>
Implement security best practices for data access and governance</div><div>
Monitor and optimize cloud costs related to data infrastructure</div><div></div><div><b><br>
Data Modeling &amp; Architecture</b></div><div>
Design and implement dimensional data models for analytics</div><div>
Build star/snowflake schemas optimized for analytical queries</div><div>
Create data marts for specific business domains (retention, campaigns, product)</div><div>
Ensure data model scalability and maintainability</div><div>
Document data lineage, dependencies, and business logic</div><div>
Implement slowly changing dimensions and historical tracking</div><div></div><div><b><br>
Orchestration &amp; Automation</b></div><div>
Build and maintain workflow orchestration using Airflow or similar tools</div><div>
Implement scheduling, monitoring, and alerting for data pipelines</div><div>
Create automated data quality validation frameworks</div><div>
Design retry logic and error handling for production pipelines</div><div>
Build CI/CD pipelines for data workflows</div><div>
Automate infrastructure provisioning using Infrastructure as Code</div><div></div><div><b><br>
Cross-Functional Collaboration</b></div><div>
Partner with Senior Data Analyst to understand analytics requirements</div><div>
Work with Growth Director and team to enable data-driven decision making</div><div>
Support CRM Lead with data needs for campaign execution</div><div>
Collaborate with Product and Engineering on event tracking and instrumentation</div><div>
Document technical specifications and best practices for the team</div><div>
Work closely with all squads , establish data contracts with engineers to land data in a most optimal way.</div><div></div><div><b><br>
Required Qualifications</b></div><div></div><div><b><br>
Must-Have Technical Skills</b></div><div><b>
Apache Spark</b>: Expert-level proficiency in PySpark/Spark SQL for large-scale data processing - this is non-negotiable</div><div><b>
Databricks</b>: Strong hands-on experience building and optimizing pipelines on Databricks platform - this is non-negotiable</div><div><b>
AWS</b>: Deep knowledge of AWS data services (S3, Glue, EMR, Redshift, Athena) - this is non-negotiable</div><div><b>
Data Modeling</b>: Proven experience designing dimensional models and data warehouses - this is non-negotiable</div><div><b>
Orchestration</b>: Strong experience with workflow orchestration tools (Airflow, Prefect, or similar) - this is non-negotiable</div><div><b>
SQL</b>: Advanced SQL skills for complex queries and optimization</div><div><b>
Python</b>: Strong programming skills for data engineering tasks</div><div></div><div><b><br>
Experience</b></div><div>
6-10 years in data engineering with focus on building scalable data platforms</div><div>
Proven track record architecting and implementing data infrastructure from scratch</div><div>
Experience processing large volumes of event data (billions of records)</div><div>
Background in high-growth tech companies or consumer-facing products</div><div>
Experience with mobile/web analytics data preferred</div><div></div><div><b><br>
Technical Requirements</b></div><div>
Expert in Apache Spark (PySpark and Spark SQL) with performance tuning experience</div><div>
Deep hands-on experience with Databricks (clusters, jobs, notebooks, Delta Lake)</div><div>
Strong AWS expertise: S3, Glue, EMR, Redshift, Athena, Lambda, CloudWatch</div><div>
Proficiency with orchestration tools: Airflow, Prefect, Step Functions, or similar</div><div>
Advanced data modeling skills: dimensional modeling, normalization, denormalization</div><div>
Experience with data formats: Parquet, Avro, ORC, Delta Lake</div><div>
Version control with Git and CI/CD practices</div><div>
Infrastructure as Code: Terraform, CloudFormation, or similar</div><div>
Understanding of data streaming technologies (Kafka, Kinesis) is a plus</div><div></div><div><b><br>
Core Competencies</b></div><div><b>
Self-sufficient</b>: You figure things out independently without constant guidance</div><div><b>
Problem solver</b>: You diagnose and fix complex data pipeline issues autonomously</div><div><b>
Performance-focused</b>: You optimize for speed, cost, and reliability</div><div><b>
Quality-driven</b>: You build robust, maintainable, and well-documented solutions</div><div><b>
Ownership mindset</b>: You take end-to-end responsibility for your work</div><div><b>
Collaborative</b>: You work well with analysts and business stakeholders despite being independent</div><div></div><div><b><br>
Nice-to-Have</b></div><div>
Databricks certifications (Data Engineer Associate/Professional)</div><div>
Experience with dbt for data transformation</div><div>
Knowledge of customer data platforms (Segment, mParticle, Rudderstack)</div><div>
Experience with event tracking platforms (Mixpanel, Amplitude)</div><div>
Familiarity with machine learning infrastructure and MLOps</div><div>
Experience in MENA region or emerging markets</div><div>
Background in on-demand services, marketplaces, or subscription businesses</div><div>
Knowledge of real-time streaming architectures</div><div></div><div><b><br>
What We Offer</b></div><div>
Competitive salary based on experience</div><div>
Ownership of critical data infrastructure and architecture decisions</div><div>
Work with modern data stack and cutting-edge AWS technologies</div><div>
Direct impact on business decisions through data platform improvements</div><div>
Comprehensive health benefits</div><br>
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<p>
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</p></div>

Senior Data Engineer

PCS Gulf

<p>PCS Gulf excels in IT and financial consulting, driven by the belief that optimal solutions arise from a diverse network of experts collaborating across IT, Finance, and business strategy. Our seasoned team remains industry leaders, staying updated on the latest trends. We provide innovative, cutting-edge solutions tailored to clients' needs, drawing from vast industry exposure. Collaborating closely, we craft comprehensive solutions addressing all aspects of business. With a stellar track record and proficiency, we empower clients, from startups to large corporations, to realize their full potential. At PCS Gulf, our unwavering dedication is to deliver tangible results.<br> </p>
 <p> <b>Responsibilities:</b> </p> <ul>
 <li>You are detailed reviewing and analysing<br> structured, semi-structured and unstructured data sources for quality,<br> completeness, and business value. </li>
 <li>You design, architect, implement and test<br> rapid prototypes that demonstrate value of the data and present them to<br> diverse audiences. </li>
 <li>You participate in early state design and<br> feature definition activities. </li>
 <li>Responsible for implementing robust data<br> pipeline using Microsoft,Databricks Stack. </li>
 <li>Responsible for creating reusable and scalable<br> data pipelines. </li>
 <li>You are a Team-Player, collaborating with team<br> members across multiple engineering teams to support the integration of<br> proven prototypes into core intelligence products. </li>
</ul> <p> <b>Requirements:</b> </p> <p>
</p> <ul>
 <li>Advanced working knowledge and experience with<br> relational and non-relational databases </li>
 <li>Experience building and optimizing Big Data<br> data pipelines, architectures, and data sets. </li>
 <li>Strong experience in Azure<br> Datafactory,Databricks, Eventhub, Python,PySpark ,Azure Synapse and SQL </li>
 <li>Azure Devops experience to deploy the ADF<br> pipelines. </li>
 <li> Minimum<br> 3-5 years of experience. </li>
 <li> Knowledge/Experience with Azure cloud<br> stack. </li>
</ul>

Azure Data Engineer

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