data analyst

technical engineer

software engineer

data scientist

senior data analyst

data engineer

ATOM Insurance

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Job description <div>
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 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. As a Data Engineer, you will: Build different types of data warehousing layers based on specific use cases Lead the design, implementation, and successful delivery of large-scale, critical, or difficult data solutions involving a significant amount of work Build scalable data infrastructure and understand distributed systems concepts from a data storage and compute perspective Utilize expertise in SQL and have a strong understanding of ETL and data modeling Ensure the accuracy and availability of data to customers and understand how technical decisions can impact their business s analytics and reporting Be proficient in at least one scripting/programming language to handle large volume data processing We are looking for 5+ years of experience in data engineering in a customer or business facing capacity. 
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Knowledge and Skills <div>
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 To be considered for this role you will have: Ability to understand and articulate requirements to technical and non-technical audiences Stakeholder management and communication skills, including prioritising, problem solving and interpersonal relationship building Strong experience in SDLC delivery, including waterfall, hybrid and Agile methodologies. Experience delivering in an agile environment Experience of implementing and delivering data solutions and pipelines on AWS Cloud Platform A strong understanding of data modelling, data structures, databases, and ETL processes An in-depth understanding of large-scale data sets, including both structured and unstructured data Strong SQL and Python knowledge Knowledge and experience of delivering CI/CD and DevOps capabilities in a data environment Basic qualifications: At least 3- 5 years of Consulting or client service delivery experience on Amazon AWS (AWS) 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 Extensive experience providing practical direction within the AWS Native and Hadoop Experience with private and public cloud architectures, pros/cons, and migration considerations 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. 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. Experience working with DevOps tools such as GitLabs, Jenkins, CodeBuild, CoePipeline CodeDeploy, etc. Bachelors or higher degree in Computer Science or a related discipline Must have at least one AWS certification: Certified AWS Developer Associate Certified AWS DevOps Professional Certified AWS Big Data Specialty Nice-to-have skills/qualifications: DevOps on an AWS platform. Multi-cloud experience a plus Experience developing and deploying ETL solutions on AWS using tools like Talend, Informatica, Matillion Strong in Java, C##, Spark, PySpark, Unix shell/Perl scripting IoT, event-driven, microservices, containers/Kubernetes in the cloud
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Data Engineer

Client of Talent Bridge HR Consultancy Dubai

Role Summary 

Build robust, observable data pipelines that power research and production AI. Success means high pipeline reliability (on-time SLAs), strong data quality (validation &amp; lineage), and enabling fast experimentation. You will partner with AI/ML, analytics, and product to make data trustworthy and usable.
 Responsibilities 
<ul>
 <li>Architect and operate batch/stream pipelines (Airflow; Spark optional) for ETL/ELT.</li>
 <li>Model/manage schemas; enforce data quality and lineage/governance.</li>
 <li>Support ML workflows with DVC (data versioning) and MLflow or Weights &amp; Biases.</li>
 <li>Build feature stores/data services; expose datasets via secure REST endpoints.</li>
 <li>Optimize performance/cost across storage/compute; implement monitoring/alerting.</li>
 <li>Maintain documentation and internal catalogs; enable self-service analytics.</li>
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 Qualifications 
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 <li> Skills: Programming in C++ or Java; SQL &amp; NoSQL; Pandas/NumPy; PySpark; Airflow; API development; Docker.</li>
 <li> MLOps: DVC; MLflow or W&amp;B; model packaging/deployment fundamentals.</li>
 <li> Cloud: AWS SageMaker, Azure ML, or GCP AI experience.</li>
 <li> Nice to have: Unreal Engine exposure.</li>
 <li> Environment: Solid Linux background for development and deployment.</li> <li> Education/Experience: Proven experience building reliable pipelines in production</li> </ul>

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:
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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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BBGC

We are a global technology consultancy firm with offices in Middle East, Asia, Europe and USA. We deliver business benefits through innovation. We leverage cutting-edge technology led solutions delivered by a team of skilled professionals, from sustainable software development to cloud services and operational excellence strategy. We have extensive expertise in Capital Markets and in particular Trading and Risk Management functions. Senior Data Engineer will play a critical role in designing, bu We are a global technology consultancy firm with offices in Middle East, Asia, Europe and USA. We deliver business benefits through innovation. We leverage cutting-edge technology led solutions delivered by a team of skilled professionals, from sustainable software development to cloud services and operational excellence strategy. We have extensive expertise in Capital Markets and in particular Trading and Risk Management functions. Senior Data Engineer will play a critical role in designing, building, and maintaining scalable data pipelines and analytics solutions using Azure and Data bricks ecosystem . Collaborate closely with business stakeholders - to ensure data is accessible, reliable, and optimized for performance. Requirements 6+ years of experience in data engineering or related roles. Proven expertise in Azure Data Factory and Azure Databricks. Strong proficiency in Python for data engineering tasks. Solid understanding of SQL and relational databases. Exposure to real-time data processing frameworks (e.g., Spark Streaming, Kafka). Experience in maintaining and supporting production-grade data pipelines. Familiarity with trading business domain, including market data, trade lifecycle, and financial instruments. Experience with version control systems (e.g., Git) and CI/CD pipelines. Excellent problem-solving skills and attention to detail.

Senior Data Engineer

Foodics

You will be responsible for architecting and building robust data pipelines, data contracts, and processing frameworks that power analytics and ML features across Foodics. You ll work closely with ML Engineers and platform teams to ensure the reliability, scalability, and governance of our data infrastructure.
What Will You Do
<ul>
 <li>Design and implement scalable ETL/ELT pipelines using cloud-native tools.</li>
 <li>Define and enforce data contracts with domain squads and internal consumers.</li>
 <li>Collaborate with ML Engineers on feature engineering and model-ready datasets.</li>
 <li>Build monitoring, alerting, and observability into the data infrastructure.</li>
 <li>Ensure data security, lineage, and compliance with internal standards.</li>
 <li>Contribute to onboarding toolkits and reusable data components.</li>
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What Are We Looking For
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 <li>5+ years of experience in data engineering, with a track record in scalable pipelines.</li>
 <li>Strong command of Python, SQL, and orchestration tools (e.g., Airflow, AWS Glue, Step Functions).</li>
 <li>Experience with modern Lakehouse architecture and tools (e.g., S3, Redshift, Snowflake, dbt).</li>
 <li>Deep understanding of data modeling, lineage, observability, and governance frameworks. (e.g., dimensional modeling, normalized vs. denormalized structures, schema evolution, ML feature stores)</li>
 <li>Familiarity with ACID-compliant data formats such as Apache Iceberg, Delta Lake, or Apache Hudi, and experience managing large-scale datasets with time travel, schema evolution, and transactional guarantees.</li>
 <li>Experience building fault-tolerant, testable, and maintainable pipelines in production environments.</li>
 <li>Proven ability to work in cross-functional teams, collaborating with ML Engineers, Analysts, and Product Managers.</li>
 <li>Familiar with CI/CD and infrastructure-as-code (Terraform/CDK preferred).</li>
 <li>Strong communication skills and a mindset focused on documentation, standards, and continuous improvement.</li>
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Who Will Excel
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 <li>Candidates with knowledge of MLOps integration and streaming technologies (e.g., Kafka, Kinesis).</li>
</ul>

<div>Who Are We&#10067; 
We Are Foodics! a leading restaurant management ecosystem and payment tech provider. Founded in 2014 with headquarter in Riyadh and offices across 5 countries, including UAE, Egypt, Jordan and Kuwait. We are currently serving customers and partners in over 35 different countries worldwide. Our innovative products have successfully processed over 6 billion (yes, billion with a B) orders so far! making Foodics one of the most rapidly evolving SaaS companies to ever emerge from the MENA region. Also Foodics has achieved three rounds of funding, with the latest raising $170 million in the largest SaaS funding round in MENA, boosting its innovation capabilities to better serve business owners.
The Job in a Nutshell
You will be responsible for architecting and building robust data pipelines, data contracts, and processing frameworks that power analytics and ML features across Foodics. You&rsquo;ll work closely with ML Engineers and platform teams to ensure the reliability, scalability, and governance of our data infrastructure.
What Will You Do&#10067;<ul>
<li>Design and implement scalable ETL/ELT pipelines using cloud-native tools.</li>
<li>Define and enforce data contracts with domain squads and internal consumers.</li>
<li>Collaborate with ML Engineers on feature engineering and model-ready datasets.</li>
<li>Build monitoring, alerting, and observability into the data infrastructure.</li>
<li>Ensure data security, lineage, and compliance with internal standards.</li>
<li>Contribute to onboarding toolkits and reusable data components.</li>
</ul>What Are We Looking For&#10067;<ul>
<li>5+ years of experience in data engineering, with a track record in scalable pipelines.</li>
<li>Strong command of Python, SQL, and orchestration tools (e.g., Airflow, AWS Glue, Step Functions).</li>
<li>Experience with modern Lakehouse architecture and tools (e.g., S3, Redshift, Snowflake, dbt).</li>
<li>Deep understanding of data modeling, lineage, observability, and governance frameworks. (e.g., dimensional modeling, normalized vs. denormalized structures, schema evolution, ML feature stores)</li>
<li>Familiarity with ACID-compliant data formats such as Apache Iceberg, Delta Lake, or Apache Hudi, and experience managing large-scale datasets with time travel, schema evolution, and transactional guarantees.</li>
<li>Experience building fault-tolerant, testable, and maintainable pipelines in production environments.</li>
<li>Proven ability to work in cross-functional teams, collaborating with ML Engineers, Analysts, and Product Managers.</li>
<li>Familiar with CI/CD and infrastructure-as-code (Terraform/CDK preferred).</li>
<li>Strong communication skills and a mindset focused on documentation, standards, and continuous improvement.</li>
</ul>Who Will Excel&#10067;<ul><li>
Candidates with knowledge of MLOps integration and streaming technologies (e.g., Kafka, Kinesis).</li></ul>
What We Offer You&#10071; 
We believe you will love working at Foodics!<ul>
<li>We have an inclusive and diverse culture that encourages innovation.</li>
<li>We offer highly competitive compensation packages, including bonuses and the potential for shares.</li>
<li>We prioritize personal development and offer regular training and an annual learning stipend to tackle new challenges and grow your career in a hyper-growth environment.</li>
<li>Join a talented team of over 30 nationalities working in 14 countries, and gain valuable experience in an exciting industry.</li>
<li>We offer autonomy, mentoring, and challenging goals that create incredible opportunities for both you and the company.</li></ul></div>

BlackStone eIT

BlackStone eIT is seeking a highly motivated Senior Data Engineer for a 2-month contract to assist in the development and optimization of our data infrastructure. This temporary role will provide the opportunity to work on critical projects and make an immediate impact within our team. As a Senior Data Engineer, you will design and implement data pipelines, ensuring the efficient processing and analysis of large sets of data. Your expertise will enhance our data management strategies and support data-driven decision-making across the organization within a tight timeframe. Key Responsibilities <ul> <li>Design and develop data pipelines for both batch and real-time data processing.</li> <li>Implement ETL processes, ensuring timely and accurate data flow from various sources.</li> <li>Optimize existing data infrastructures for improved performance and accessibility.</li> <li>Collaborate closely with data analysts and business stakeholders to understand their data needs.</li> <li>Conduct data quality assessments and implement solutions to improve data integrity.</li> <li>Document processes and workflows for future reference.</li> <li>Quickly troubleshoot and resolve any data-related issues that arise.</li> </ul>

Senior Data Engineer (2-Months) Contract

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Senior Data Engineer (2-Months) Contract