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Halan - حالا

<div>
 
 Job Overview:
 
 
 We are seeking a talented and motivated Senior Data Engineer with expertise in Scala and Python to join our data engineering team. This individual will play a key role in the design, development, and optimization of our data infrastructure and data pipelines. The ideal candidate has a passion for building scalable, high-performance systems and is eager to broaden their knowledge across the entire data engineering stack, from hardware infrastructure to project development.
 
 
 Key responsibilities:
 
 
 &bull; Collaborate with cross-functional teams to design, develop, and maintain data engineering solutions using Scala, Python, and Apache Spark.
 
 
 &bull; Implementation of new data engineering technologies, frameworks, and tools, such as HDFS, MongoDB, and PostgreSQL, to enhance performance, scalability, and efficiency.
 
 
 &bull; Understand and optimize hardware and resource consumption for data engineering projects.
 
 
 &bull; Develop a deep understanding of hardware infrastructure, including servers, clusters, and distributed systems, to ensure optimal data processing and storage.
 
 
 &bull; Design and architect high-performance, fault-tolerant, and scalable data pipelines.
 
 
 &bull; Conduct research and stay current with the latest advancements in data engineering, hardware technologies, and distributed computing paradigms.
 
 
 &bull; Mentor and guide junior team members, fostering a culture of continuous learning and skill development.
 
 
 &bull; Collaborate with stakeholders to gather requirements, propose technical solutions, and deliver high-quality data engineering projects.
 
 
 Requirements:
 
 
 &bull; 2-3 years of professional experience as a Software Engineer, with a focus on data engineering.
 
 
 &bull; Keen interest in hardware infrastructure, resource consumption optimization, and data engineering project development.
 
 
 &bull; Proven ability to work effectively in an Agile development environment and manage multiple priorities.
 
 
 &bull; Strong problem-solving, analytical thinking, communication, and collaboration skills.
 
</div>

Data Engineer

QNBeyond Plus

<div>
 
 About the Role
 
 
 We are looking for a motivated
 
 Data Engineer
 
 to join our
 
 Data Management and AI team
 
 and contribute to building scalable data platforms that power analytics and AI initiatives across our digital banking ecosystem.
 
 
 In this role, you will design and develop
 
 data pipelines, streaming infrastructure, and data warehouse solutions
 
 that enable reliable and high-performance data processing.
 
 
 This is an excellent opportunity for a
 
 junior data engineer
 
 looking to grow within a fast-paced fintech environment while working on modern data technologies.
 
 
 Team Overview
 
 
 The
 
 Data Management and AI team
 
 works across the entire technology stack within QNBeyond Plus.
 
 
 Our team collaborates with engineering, analytics, and product teams to manage, process, and analyze data that enables innovative digital banking experiences for our customers.
 
 
 Key Responsibilities
 
 
 Data Pipeline Development
 
 <ul>
 <li>
 Design and build scalable
 
 data pipelines for batch and real-time processing
 
 .
 </li>
 <li>
 Implement ETL/ELT workflows integrating data from
 
 APIs, databases, and event streams
 
 .
 </li>
 </ul>
 
 Streaming &amp; Event Processing
 
 <ul>
 <li>
 Develop and maintain
 
 streaming data pipelines using tools such as Kafka or similar platforms
 
 .
 </li>
 <li>
 Ensure
 
 low-latency, reliable, and fault-tolerant data delivery
 
 .
 </li>
 </ul>
 
 Data Transformation
 
 <ul>
 <li>
 Develop
 
 data enrichment and transformation workflows
 
 to convert raw data into business-ready datasets.
 </li>
 <li>
 Implement SQL transformations across layered architectures (
 
 raw &rarr; bronze &rarr; silver &rarr; gold
 
 ).
 </li>
 </ul>
 
 Data Warehouse Development
 
 <ul>
 <li>
 Design and maintain
 
 data warehouse models and schemas
 
 .
 </li>
 <li>
 Optimize query performance and storage design for analytical workloads.
 </li>
 </ul>
 
 Data Quality &amp; Reliability
 
 <ul>
 <li>
 Implement
 
 data validation and quality checks
 
 .
 </li>
 <li>
 Monitor data pipeline performance and ensure reliability.
 </li>
 </ul>
 
 Collaboration
 
 <ul>
 <li>
 Work closely with
 
 engineering, analytics, and product teams
 
 to deliver production-ready data solutions.
 </li>
 </ul>
 
 What We Are Looking For
 
 
 You must be:
 
 <ul>
 <li>
 
 Self-motivated
 
 , proactive, and results-driven
 </li>
 <li>
 A
 
 team player
 
 who enjoys collaboration and learning
 </li>
 <li>
 A
 
 problem solver
 
 who approaches challenges analytically
 </li>
 <li>
 
 Customer-oriented
 
 , committed to delivering high-quality data solutions
 </li>
 <li>
 
 Detail-oriented
 
 , especially regarding data quality and compliance
 </li>
 <li>
 Adaptable and eager to grow in a
 
 fast-paced fintech environment
 
 </li>
 </ul>
 
 Required Qualifications
 
 
 Education
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in
 
 Computer Science, Computer Engineering, or related field
 
 </li>
 </ul>
 
 Technical Knowledge
 
 <ul>
 <li>
 Understanding of
 
 computer systems and cloud environments
 
 </li>
 <li>
 Understanding of
 
 network protocols and system connectivity
 
 </li>
 </ul>
 
 Systems Skills
 
 <ul>
 <li>
 Experience using
 
 Linux command line tools
 
 </li>
 <li>
 Familiarity with
 
 SSH, SFTP, Bash, IP, ports, and networking concepts
 
 </li>
 </ul>
 
 Data Engineering Skills
 
 <ul>
 <li>
 Experience developing and optimizing
 
 ETL/ELT pipelines
 
 </li>
 <li>
 Experience with tools such as
 
 Informatica PowerCenter, Kafka, NiFi, or similar
 
 </li>
 </ul>
 
 Data &amp; Analytics
 
 <ul>
 <li>
 Strong
 
 SQL skills
 
 </li>
 <li>
 Understanding of
 
 data warehousing concepts and schema design
 
 </li>
 <li>
 Experience with
 
 data modeling and data lifecycle management
 
 </li>
 </ul>
 
 Programming
 
 <ul>
 <li>
 Programming experience using
 
 Python
 
 </li>
 <li>
 Scripting experience using
 
 Bash or similar tools
 
 </li>
 </ul>
 
 Experience
 
 <ul>
 <li>
 
 2+ years of experience working with ETL or data engineering workflows
 
 </li>
 <li>
 Experience with
 
 Informatica PowerCenter and MDM
 
 </li>
 <li>
 Experience developing and scaling
 
 data models within modern data warehouse architectures
 
 </li>
 <li>
 Experience implementing
 
 data enrichment and transformation logic
 
 </li>
 <li>
 Experience optimizing queries and storage design for analytics workloads
 </li>
 <li>
 At least
 
 1 year of experience in fintech, regulated environments, or PCI/DSS compliance
 
 is preferred
 </li>
 <li>
 Familiarity with
 
 performance monitoring tools
 
 </li>
 </ul>
</div>

TAQA Water

<div>
 
 About The Job Junior Data Engineer
 
 
 
 As a Junior Data Engineer, you will be responsible for supporting the design, development, and maintenance of our data infrastructure. You will work closely with key users to identify efficient data processing and analysis of large datasets.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Assist in the design and implementation of data pipelines.
 </li>
 <li>
 Develop and maintain PySpark notebooks for data processing and analysis.
 </li>
 <li>
 Support the integration and management of data from various sources, including dataflows and data lakes.
 </li>
 <li>
 Work with both structured and unstructured data to ensure comprehensive data coverage.
 </li>
 <li>
 Collaborate with team members to optimize data workflows and improve data quality.
 </li>
 <li>
 Monitor and troubleshoot data processing systems to ensure reliability and performance.
 </li>
 <li>
 Document data processes and workflows for future reference.
 </li>
 <li>
 Stay updated with the latest industry trends and technologies in data engineering.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Information Technology, or a related field from1 to 2 years' experience
 </li>
 <li>
 Proficiency in PySpark and Python programming.
 </li>
 <li>
 Knowledge of Microsoft Fabric components and their application in data engineering.
 </li>
 <li>
 Familiarity with SQL and database management systems, including data warehouses.
 </li>
 <li>
 Familiarity with data gateways for secure data transfer.
 </li>
 <li>
 Strong problem-solving skills and attention to detail.
 </li>
 <li>
 Excellent communication and teamwork abilities.
 </li>
 </ul>
</div>

Junior Data Engineer

Koinz

<div>
 
 About Koinz:
 
 
 
 Koinz is a fast-growing social ecommerce mobile app specializing in food ordering and innovative loyalty programs across the MENA region, notably in Saudi Arabia and Egypt. We're dedicated to enhancing our users&rsquo; experiences through seamless, engaging, and rewarding interactions.
 
 
 
 Role brief:
 
 
 
 We are seeking a highly skilled and motivated Senior Data Engineer to join our dynamic and growing team. You will be instrumental in designing, developing, and optimizing our next-generation data infrastructure, driving key business insights.
 
 
 
 What You'll Bring:
 
 
 
 <ul>
 <li>
 3+ years of professional experience in data engineering or a related field
 </li>
 <li>
 Proficiency in developing data processing jobs using Apache Spark
 </li>
 <li>
 Experience with workflow orchestration tools, specifically Apache Airflow, including designing and maintaining complex DAGs
 </li>
 <li>
 Strong programming skills in Python (including data-related libraries like Pandas, NumPy) for scripting, automation, and ETL/ELT development
 </li>
 <li>
 Mastery of SQL for complex querying, data modeling, and performance tuning in various relational databases
 </li>
 <li>
 Solid understanding of data warehousing concepts, ETL/ELT principles, and dimensional modeling
 </li>
 <li>
 Excellent problem-solving skills and the ability to work independently and as part of a team
 
 
 </li>
 </ul>
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Design, build, and maintain efficient, scalable, and reliable data pipelines using Spark, Python, and Airflow
 </li>
 <li>
 Develop optimal SQL queries and stored procedures to ensure data quality and integrity
 </li>
 <li>
 Collaborate with data analysts to understand data needs and deliver data sets that power business decisions and machine learning models
 </li>
 <li>
 Implement robust monitoring, alerting, and logging for all data pipelines to ensure high operational stability
 </li>
 <li>
 Optimize data architecture for performance, cost-efficiency, and security
 
 
 </li>
 </ul>
 Powered by JazzHR
 
 
 PJ7GmyHdvJ
</div>

Senior Data Engineer

Coca-Cola HBC

<div>
 
 
 Department:
 
 Data, Insights &amp; Artificial Intelligence (DIAI)
 
 
 
 Location:
 
 Egypt, Bulgaria, Greece
 
 
 
 
 
 As a Product Expert for Data Control &amp; Data Quality, you will play a key role in the design, build, configuration, monitoring and continuous improvement of Coca-Cola Hellenic&rsquo;s Data Quality Management products, with a primary focus on the Data Control Center (DCC). You will work closely with the Data Quality &amp; Standards Product Manager, Business Stakeholders, Business Unit Data Stewards and IT partners (DTPS), ensuring that data quality controls, monitoring and reporting enable reliable and trusted data across the organization. This is a hands-on data engineering role requiring strong technical skills in SQL, PySpark and Azure-based data platforms and the emerging AI and GenAI techniques, combined with full ownership of deliverables from production support and the flexibility to handle ad-hoc requests and parallel priorities while translating business requirements into scalable, automated and intelligent data quality solutions.
 
 
 
 
 
 
 YOUR NEW KEY RESPONSIBILITIES
 
 
 
 
 Data Quality Controls (DCC)
 
 
 
 &bull; Lead the design and end-to-end ownership of Data Quality controls in the Data Control Center (DCC), from implementation through production support and continuous improvement
 
 
 &bull; Translate business requirements into data quality rules, including logic definition, thresholds, exception handling and reduction of false positives
 
 
 &bull; Discover the possibility of AI solutions for advanced checks and/or smart data errors remediation.
 
 
 &bull; Ensure DQ controls are aligned with agreed business definitions and standards.
 
 
 
 
 
 
 Monitoring, Operations &amp; Issue Resolution
 
 
 
 &bull; Monitor DQ performance and ensure stable DCC operations, including regular refresh cycles and system reliability.
 
 
 &bull; Troubleshoot failed checks, investigate data issues and perform root-cause analysis in collaboration with relevant stakeholders.
 
 
 &bull; Support incident resolution and contribute to continuous operational improvements.
 
 
 
 
 
 
 Continuous Improvement &amp; Enhancement
 
 
 
 &bull; Implement improvements to existing DQ checks and contribute to the continuous enhancement of DCC capabilities.
 
 
 &bull; Identify opportunities to improve automation, intelligence, scalability and reusability of controls and monitoring processes.
 
 
 &bull; Identify opportunities to automate monitoring and reduce manual effort for stakeholders.
 
 
 
 
 
 
 Reporting &amp; Dashboards
 
 
 
 &bull; Develop and maintain DQ dashboards and scorecards, enabling visibility of DQ KPIs, trends and drilldowns.
 
 
 &bull; Support stakeholders with insights and reporting to track performance and drive quality improvement actions.
 
 
 
 
 
 
 Data Standards Operationalization
 
 
 
 &bull; Support data standards operationalization by ensuring alignment between published standards and DQ checks.
 
 
 &bull; Support adoption and compliance visibility by enabling reporting and transparency on standards adherence.
 
 
 
 
 
 
 Collaboration &amp; Delivery Support
 
 
 
 &bull; Work closely with the Product Manager and business stakeholders to clarify requirements, validate solutions and ensure high usability and adoption.
 
 
 &bull; Collaborate with DTPS and vendors to deliver end-to-end solutions, including integration dependencies and technical enablement.
 
 
 &bull; Run demos and workshops when needed to support rollout, stakeholder understanding and adoption.
 
 
 
 
 
 
 Testing, Release &amp; Documentation
 
 
 
 &bull; Support release and testing activities, including UAT support and regression testing.
 
 
 &bull; Maintain basic documentation of implemented DQ checks, logic, definitions and changes.
 
 
 
 
 
 
 
 
 
 ARE THESE YOUR SECRET INGREDIENTS?
 
 
 
 &bull; 3+ years in data engineering / data science /analytics engineering / data quality engineering
 
 
 &bull; Strong SQL and Python for scalable data validation and monitoring
 
 
 &bull; Experience working with Databricks and modern data pipelines (ADF or similar)
 
 
 &bull; Strong analytical and problem-solving mindset with attention to detail and quality.
 
 
 &bull; Ability to translate business requirements into technical implementation and measurable outcomes.
 
 
 &bull; Comfortable working across multiple stakeholders in a cross-functional environment.
 
 
 &bull; Strong communication skills and ability to explain technical topics to non-technical audiences.
 
 
 &bull; Ownership mindset: proactive, reliable and continuously improving solutions.
 
 
 
 
 
 
 REQUIRED TECHNICAL SKILLS
 
 
 
 &bull; SQL
 
 
 &bull; Python
 
 
 &bull; PySpark
 
 
 &bull; Azure Databricks
 
 
 &bull; Azure Data Factory
 
 
 &bull; Power BI
 
 
 &bull; Machine Learning
 
 
 &bull; AI/ GenAI
 
 
 
 
 
 
 NICE TO HAVE
 
 
 
 &bull; Power Platform (Power Automate, etc.)
 
 
 &bull; Microsoft Fabric
 
 
 &bull; Copilot Studio
 
 
 &bull; Experience working in a Data Mesh framework and/or domain data product mindset
 
 
 &bull; Good awareness of key SAP MDG, MM, S/4HANA domains
 
 
 
 
 
 
 ABOUT YOUR NEW TEAM:
 
 
 
 We are Coca-Cola Hellenic, a growth-focused consumer goods business and strategic bottling partner of the Coca-Cola Company. We bottle, distribute and sell an unrivalled range of products in 29 markets in Europe, Africa and Eurasia. As we do, we create value for all stakeholders, support socio-economic growth and build a more positive environmental impact.
 
 
 We bring together more than 30,000 people from over 70 nationalities, coming from five continents. The diversity of our markets, from mature to emerging economies, provides a wide range of attractive opportunities for growth.
 
 
 We nurture our talents. We give opportunities to people across all functions and levels, as well as different geographies, backgrounds and education. We are willing to take a risk on the people we believe in, even if they don&rsquo;t have the perfect experience. We have faith in what every person can be.
 
 
 And although we have so much to be proud of, we always stay humble. We believe the real magic happens - for us and for you - when we OPEN UP.
 
 
 
 
 
 
 AT COCA-COLA HBC, DIVERSITY HELPS US THRIVE
 
 
 
 At Coca-Cola HBC, we are an inclusive employer that thrives on diversity. This means our environment provides equal opportunities for all, regardless of race, color, religion, age, disability, sexual orientation, or gender identity. Join us in nurturing a culture where everyone belongs and contributes to our collective success.
 
 
 
 
</div>

Oscar

<div>
 
 
 Cairo, Egypt (Hybrid - 4 days onsite)
 
 
 
 
 650,000 EGP - 1,400,000 EGP base salary (DOE)
 
 
 
 
 Full-time | Permanent
 
 
 
 
 ( + Transportation Allowance + Strong benefits package)
 
 
 
 
 
 
 
 
 About the Company
 
 
 
 
 
 
 
 We have partnered with a large, internationally recognised manufacturing, distribution, and sales organisation operating across multiple global markets. With a strong focus on digital transformation, data-driven decision making, and modern cloud platforms, they are investing heavily in enterprise analytics, reporting, and scalable data solutions that support both operational and strategic outcomes.
 
 
 
 
 
 
 
 The Role
 
 
 
 
 
 
 
 The organisation is seeking an experienced
 
 Senior Azure Data Engineer / Developer
 
 to join its Digital &amp; Technology function, working closely with BI and Reporting teams. This role plays a critical part in designing, building, and optimising Azure-based data pipelines and analytical solutions that serve as a single source of truth for enterprise and operational reporting.
 
 
 The successful candidate will collaborate with business stakeholders, analysts, and engineers to integrate and transform data from multiple systems into high-quality, trusted datasets that power Power BI dashboards and analytics products.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, develop, and maintain
 
 ETL pipelines
 
 using
 
 Azure Data Factory
 
 </li>
 <li>
 Ingest and transform data from multiple source systems into
 
 Azure Data Lake Storage
 
 and
 
 Azure SQL
 
 </li>
 <li>
 Work with large-scale datasets (terabytes of data, partitioned tables, high-volume files)
 </li>
 <li>
 Build and optimise data solutions using
 
 Databricks, Spark, Hive
 
 , and
 
 PySpark
 
 </li>
 <li>
 Ensure data quality, integrity, availability, and performance across reporting layers
 </li>
 <li>
 Support BI teams by delivering certified datasets for
 
 Power BI
 
 consumption
 </li>
 <li>
 Collaborate with data scientists, analysts, and platform teams on data requirements
 </li>
 <li>
 Contribute to cloud best practices, DevOps processes, and CI/CD pipelines
 </li>
 <li>
 Mentor junior team members and contribute to technical decision-making (senior level)
 </li>
 </ul>
 
 
 
 
 
 Required Skills &amp; Experience
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Information Technology, Data Science, or a related discipline (or 7+ years of equivalent hands-on experience in a technical data-focused role)
 </li>
 <li>
 3&ndash;5+ years of hands-on experience working with Azure Data Factory and Azure Data Lake Storage in production environments
 </li>
 <li>
 Proven experience delivering data solutions at scale, working with large and complex datasets (terabytes of data, partitioned tables, high-volume files)
 </li>
 <li>
 Strong hands-on experience with Power BI, including DAX and Power Query M
 </li>
 <li>
 Solid experience with Azure SQL Database and advanced T-SQL
 </li>
 <li>
 Practical experience with Databricks, Spark, Hive, and PySpark for big data processing
 </li>
 <li>
 Strong programming skills in Python, C#, .NET, Scala, or Java
 </li>
 <li>
 Experience working with cloud platforms, preferably Microsoft Azure (experience with AWS or GCP is a plus)
 </li>
 <li>
 Good understanding of DevOps principles and experience working with CI/CD pipelines
 </li>
 <li>
 Demonstrated ability to collaborate with business and technical stakeholders to translate requirements into scalable data solutions
 </li>
 <li>
 Strong analytical, problem-solving, and communication skills
 </li>
 <li>
 Professional working proficiency in English
 </li>
 </ul>
 
 
 
 
 
 Nice to Have
 
 
 <ul>
 <li>
 Experience with
 
 DevSecOps
 
 practices
 </li>
 <li>
 Exposure to
 
 SAFE / Agile
 
 delivery environments
 </li>
 <li>
 Knowledge of
 
 SAP BW
 
 or enterprise ERP data sources
 </li>
 <li>
 Previous leadership or mentoring experience
 </li>
 </ul>
 
 
 
 
 
 What&rsquo;s on Offer
 
 
 <ul>
 <li>
 Competitive salary:
 
 650,000 EGP - 1,400,000 EGP
 
 , depending on experience
 </li>
 <li>
 
 Hybrid working model
 
 (4 days onsite in Cairo)
 </li>
 <li>
 Private healthcare, annual bonus plus more benefits
 </li>
 <li>
 Transportation / Car Allowance
 </li>
 <li>
 Long-term career growth in a stable, well-funded organisation
 </li>
 </ul>
 
 
</div>

Azure Data Engineer / Developer

Interact Technology Solutions

<div>
 
 Job Summary
 
 
 
 The
 
 Senior AI Data Engineer
 
 is responsible for designing, building, and optimizing enterprise-scale data and AI infrastructure to support machine learning models, generative AI applications, and real-time analytics. The role drives the development of end-to-end data pipelines, from ingestion to production-ready AI data products, ensuring scalability, performance, and compliance across multi-cloud environments.
 
 
 
 Accountability &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and maintain scalable ETL/ELT data pipelines using modern data engineering tools (e.g., Apache Spark, dbt).
 </li>
 <li>
 Architect and implement Lakehouse data platforms (Delta Lake, Apache Iceberg, Apache Hudi) following Medallion architecture (Bronze/Silver/Gold).
 </li>
 <li>
 Develop real-time streaming pipelines using Apache Kafka, Apache Flink, and Spark Structured Streaming.
 </li>
 <li>
 Build and optimize AI/GenAI data pipelines for LLM training, fine-tuning, and inference (tokenization, dataset curation, prompt engineering datasets).
 </li>
 <li>
 Design and implement Retrieval-Augmented Generation (RAG) pipelines, including embedding workflows and vector database integration.
 </li>
 <li>
 Manage feature stores for real-time and batch machine learning use cases.
 </li>
 <li>
 Integrate data pipelines with AI/ML platforms (Databricks MLflow, Azure ML, AWS SageMaker, Vertex AI, OpenAI/Azure OpenAI).
 </li>
 <li>
 Implement data orchestration workflows using Apache Airflow or similar tools with CI/CD pipelines.
 </li>
 <li>
 Ensure data quality, governance, and security using frameworks such as Great Expectations and data catalog tools.
 </li>
 <li>
 Deploy and manage infrastructure using Infrastructure-as-Code tools (Terraform, Bicep, CDK).
 </li>
 <li>
 Collaborate with Data Scientists, ML Engineers, and Solution Architects to deliver production-ready AI solutions.
 </li>
 <li>
 Lead technical design decisions, mentor junior engineers, and contribute to data platform strategy.
 </li>
 <li>
 Maintain documentation, data contracts, and operational runbooks for all pipelines.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 1
 
 &ndash; Required Experience
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Engineering, or related field.
 </li>
 <li>
 4&ndash;5 years of experience in data engineering, with strong exposure to AI/ML data infrastructure.
 </li>
 <li>
 Proven experience building scalable data pipelines and working with large-scale datasets.
 </li>
 <li>
 Hands-on experience with AI/ML platforms and modern data architectures.
 </li>
 <li>
 Experience in regulated industries (e.g., Banking, Telecom, Healthcare) is a plus.
 </li>
 <li>
 Strong problem-solving, analytical thinking, and communication skills.
 </li>
 <li>
 Experience working in cross-functional teams and agile environments.
 
 
 </li>
 </ul>
 
 2&ndash; Technical Skills
 
 
 
 <ul>
 <li>
 Strong SQL and advanced data modeling techniques
 </li>
 <li>
 Apache Spark (PySpark, Spark SQL, Streaming)
 </li>
 <li>
 Python (pandas, PySpark, data processing libraries)
 </li>
 <li>
 Data pipeline orchestration (Apache Airflow)
 </li>
 <li>
 CI/CD for data pipelines (GitHub Actions / Azure DevOps)
 </li>
 <li>
 Lakehouse architectures (Delta Lake / Iceberg / Hudi)
 </li>
 <li>
 Streaming technologies (Kafka, Flink)
 </li>
 <li>
 Cloud platforms (AWS / Azure / GCP)
 </li>
 <li>
 Vector databases (Pinecone, Weaviate, pgvector, OpenSearch)
 </li>
 <li>
 RAG pipeline design and LLM data processing
 </li>
 <li>
 Infrastructure-as-Code (Terraform / Bicep / CDK)
 </li>
 <li>
 Containers (Docker, Kubernetes)
 </li>
 <li>
 Data quality &amp; governance tools
 </li>
 </ul>
</div>

Senior AI Data Engineer

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412 data engineer jobs In Cairo

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Azure Data Engineer / Developer

Senior AI Data Engineer