senior ai engineer

data scientist

machine learning engineer

devops engineer

senior data scientist

data engineer

Al-Futtaim

<div>Job Requisition ID: 176818
Established in the 1930s as a trading business, Al-Futtaim Group today is one of the most diversified and progressive, privately held regional businesses headquartered in Dubai, United A&rdquo;rab Emirates. Structured into five operating divisions; automotive, financial services, real estate, retail and healthcare; employing more than 35,000 employees across more than 20 countries in the Middle East, Asia and Africa, Al-Futtaim Group partners with over 200 of the world's most admired and innovative brands. Al-Futtaim Group&rsquo;s entrepreneurship and relentless customer focus enables the organisation to continue to grow and expand; responding to the changing needs of our customers within the societies in which we operate.
By upholding our values of respect, excellence, collaboration and integrity; Al-Futtaim Group continues to enrich the lives and aspirations of our customers each and every day. 

Overview Of The Role:

The Data Engineer is responsible for turning complex data from SAP and non-SAP sources into valuable business insights. This role involves participating in requirement assessments, implementing high-quality data solutions, and supporting various business needs. Success entails effective collaboration with product and development teams to deliver scalable, governed data solutions swiftly. The Data Engineer plays a key role in maintaining the quality of data insights solutions and ensuring alignment with business objectives. 


What You Will Do:
<ul>
<li>Partner with product owners, scrum masters, and solution architects to deliver solutions.</li>
<li>Review and analyze business requirements to design technical solutions.</li>
<li>Collaborate with implementation team members and partners internally and externally to develop, test, and deploy solutions.</li>
<li>Adhere to software development and maintenance standards by understanding development best practices.</li>
<li>Implement robust data pipelines using the Microsoft toolset and Databricks.</li>
<li>Create reusable and scalable data pipelines.</li>
<li>Estimate and deliver multiple project assignments and system change requests within agreed resourcing and timelines.</li>
<li>Govern solutions and assess complex new data sources with various SAP and non-SAP systems.</li>
<li>Analyze structured, semi-structured, and unstructured data sources for quality, completeness, and business value.</li>
<li>Govern the technology implementation of solution designs.</li></ul> 
 
Required Skills To Be Successful:
<ul>
<li>Expertise in data ingestion, data processing, and analytical pipelines for big data and data warehouse solutions.</li>
<li>Experience in cloud-based analytics solutions, particularly Azure Synapse Analytics, ADLS, ADF, Databricks, Power BI, and Azure Analysis Services.</li>
<li>Strong analytic skills with experience handling unstructured datasets.</li>
<li>Thorough understanding of DevOps processes, CI/CD, and Infrastructure as code.</li></ul> 
 
What Equips You For The Role:
<ul>
<li>8+ years of experience in Azure and Databricks.</li>
<li>Minimum 5+ years in implementing analytics capabilities from conceptualization to delivery on the Azure platform.</li>
<li>Bachelor's degree in Computer Science or a related field.</li>
<li>Knowledge of SAP BW/BO, Tableau, Power BI, and Scala is advantageous.</li>
<li>Certification on Azure platform toolsets is a beneficial addition.</li></ul> 
We&rsquo;re here to provide excellent service but a little help from you can ensure a five-star candidate experience from start to finish. 

Before you click &ldquo;apply&rdquo;: Please read the job description carefully to ensure you can confidently demonstrate why this opportunity is right for you and take the time to put together a well-crafted and personalised CV to further boost your visibility. Our global Talent Acquisition team members are all assigned to specific businesses to ensure that we make the best matches between talent and opportunities. We not only consider the requisite compatibility of skills and behaviours, but also how candidates align with our Values of Respect, Integrity, Collaboration, and Excellence. 

As part of our candidate experience promise, we also want to make ourselves available to you throughout the application process. We make every effort to review and respond to every application.</div>

Data Engineer

Bizimply

<div><h3 class="jobSectionHeader">Description</h3><div> 
About Bizimply</div><div></div><div> 
Bizimply is a workforce management platform designed to streamline operations for businesses in the hospitality, retail, and leisure industries. The Bizimply platform provides a comprehensive suite of tools that enable businesses to efficiently manage their workforce, including scheduling, time and attendance tracking, task management, HR and performance reporting. By centralising these functions in one user-friendly interface, Bizimply helps businesses save time, reduce administrative overhead, and improve overall operational efficiency.</div><div></div><div> 
We&rsquo;re looking for a Data Engineer to help us extend the foundational data infrastructure that will power the next phase of growth, including our AI initiatives. You&rsquo;ll be joining a small, enthusiastic team so we&rsquo;re looking for someone who can both build and support, excited by the challenge of laying down best practices and helping shape our new data stack. 
</div><div>Your primary focus will be on extending Bizimply&rsquo;s Data Store (ODS) and laying the groundwork for a future Data Warehouse. You'll work closely with our senior data engineer, as well as software engineering and product teams to enable better decision-making and intelligent automation.</div><h3 class="jobSectionHeader"> 
Key Responsibilities</h3> 
<ul>
<li>
Build and maintain robust, scalable data pipelines using Airflow, Python, and SQL.</li>
<li>Design, build, optimize data pipelines using dbt, or sqlmesh.</li>
<li>Develop and manage the ODS and support the eventual rollout of a modern Data Warehouse.</li>
<li>Integrate data from internal systems and external APIs to create clean, reliable datasets.</li>
<li>Work closely with engineers to operationalize machine learning workflows.</li>
<li>Ensure high data quality through monitoring, validation, and error handling.</li>
<li>Provide guidance to less experienced team members and champion data engineering best practices.</li>
<li>Deploy and manage infrastructure in the cloud (AWS, GCP, or Azure) using modern DevOps tooling.</li>
<li>Implement monitoring and alerting to ensure data pipelines are reliable and maintainable.</li></ul> 
<h3 class="jobSectionHeader">
Skills, Knowledge and Expertise</h3> 
<ul>
<li>
At least 5 years of experience in data engineering or related roles.</li>
<li>Strong skills in Python, SQL, and Airflow or similar orchestration tools.</li>
<li>Experience working with cloud infrastructure and data warehousing tools (e.g., Snowflake, BigQuery, Redshift).</li>
<li>Exposure to ML pipelines or collaboration with ML/AI teams.</li>
<li>Ability to work independently while supporting a less-experienced team.</li>
Strong communication skills and an eagerness to mentor and share knowledge 
<li>
</li></ul><ul><li>Experience building an ODS or Data Warehouse from scratch.</li>
<li>Familiarity with event-driven systems or streaming tools (e.g., Kafka, Pub/Sub).</li>
<li>DevOps experience or infrastructure-as-code (e.g., Terraform, CloudFormation).</li></ul> 
<h3 class="jobSectionHeader">
Benefits</h3> 
<ul>
<li>
Competitive compensation aligned with relevant experience.</li>
<li>Remote-friendly, flexible work environment.</li>
<li>Budget for learning, courses, and conferences.</li>
<li>A supportive, mission-driven team eager to grow and learn together.</li></ul> 
<h3 class="jobSectionHeader">
About Bizimply</h3><div>
Bizimply is a multi-platform solution born in the world of cafes, bars, restaurants and pubs, where getting your wage spend right is crucial. We&rsquo;ve been transforming hospitality scheduling in the UK and Ireland for over a decade. Our shared experience gave us the expertise to help create spot-on staff rotas and keep everything compliant, giving our customers more bandwidth to focus on what&rsquo;s important. 
Our intuitive design ensures that every manager has the tools to hit their sales per labour hour goals, with a complete view of their day-to-day operations. From streamlined scheduling to effortless compliance, we make every shift run like clockwork. 
At Bizimply, you'll have the opportunity to grow your career, gain hands-on experience, and be part of a team that&rsquo;s revolutionising the hospitality industry.</div></div>

Valleysoft

<div>Valleysoft | Center of Excellence is a regional IT services provider based in Egypt, serving clients globally since 2006. The company collaborates with global partners like Oracle to address diverse business and technical challenges, from enterprise application development to process management. Valleysoft's vendor-neutral and process-oriented approach, coupled with operational maturity, ensures high-quality and cost-effective services for clients.
Job description:<ul><li>
Build and maintain data warehouse and data marts, including ODS and internal departmental marts.</li><li>
Gather, process, maintain, and analyze large datasets, ensuring data accuracy and quality.</li><li>
Design, automate, and support ETL pipelines and data flows across multiple applications.</li><li>
Create logical and physical data flow models and mapping designs for ETL processes.</li><li>
Strong SQL skills (performance tuning, index management) and solid understanding of database structures.</li><li>
Strong understanding of data modeling concepts.</li><li>
Familiarity with SQL and NoSQL storage, and Big Data technologies (Hive, Impala, YARN, Kafka, etc.).</li></ul> 

Requirements 
Informatica-specific requirements:<ul><li>
3+ years of professional experience in Data Engineering, including ETL pipelines, data modeling, and data warehouse environments.</li></ul><ul><li>
Hands-on experience with Informatica PowerCenter development (mappings, sessions, workflows).</li><li>
Strong knowledge of Informatica transformations (e.g., Lookup, Joiner, Aggregator, Expression, Router, Sorter) and performance tuning.</li><li>
Experience with Informatica Developer.</li><li>
Experience with Informatica B2B is a plus.</li><li>
Ability to design, automate, monitor, and troubleshoot ETL jobs, including scheduling.</li></ul> 
Banking sector requirements (preferred):<ul><li>
Previous experience in the banking sector, preferably business banking, including working with banking datasets.</li><li>
Strong understanding of data quality and reconciliation expectations in banking environments.</li><li>
Experience working under regulated environments and change control practices is a strong plus.</li></ul></div>

Paymob

<div>
 Building robust and scalable data infrastructure and systems. Participating in the development of data pipelines, data models, and data integration solutions, ensuring the efficient processing, storage, and analysis of large volumes of data. Collaborating closely with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and implement solutions that enable effective data-driven decision-making.&nbsp;
 
 
 RESPONSIBILITIES
 
 <ul>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Design, build, and maintain scalable and efficient data pipelines for extracting, transforming, and loading (ETL) data from various sources into target systems, data warehouses, or data lakes. Ensure the reliability, performance, and integrity of data pipelines.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Develop data integration pipelines to consolidate data from multiple sources, ensuring data consistency and accuracy.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Implement data transformation processes to convert and cleanse data according to defined business rules and data quality standards. Handle data cleansing, data standardization, and data enrichment tasks to improve data quality and usability.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Establish and maintain scalable data storage systems such as relational databases, NoSQL databases, or cloud-based data warehouses. Optimize data storage and retrieval for efficient data processing and analysis.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Utilize big data technologies and frameworks such as Apache Hadoop, Apache Spark, or cloud-based services like Amazon Redshift, DMS&hellip;etc. to handle large volumes of structured and unstructured data. Implement distributed computing techniques for parallel processing and high-performance data processing.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Develop and implement data quality assurance processes, including data validation rules, data profiling, and data quality monitoring. Identify and address data quality issues, anomalies, or inconsistencies in a proactive and timely manner to decide as per high quality data.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Monitor and optimize data pipelines, data processing workflows, and data storage systems for performance and efficiency. Identify and resolve bottlenecks, optimize queries, and tune data processing operations for improved system performance to avoid any system failures.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand their data requirements and provide technical expertise. Document data engineering processes, data flows, and system configurations for knowledge sharing and future reference.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Stay updated with emerging technologies, trends, and best practices in the field of data engineering, continuously learn and evaluate new tools, techniques, and frameworks to improve data engineering capabilities and drive innovation.&nbsp;&nbsp;
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Drive operational excellence by overseeing daily data pipelines and infrastructure, ensuring optimal performance, reliability, and scalability. Proactively monitor and address potential issues, implement best practices, and continuously improve data workflows to enhance efficiency and system stability.
 </li>
 <li>
 
 
 
 </li>
 </ul>
 
 REQUIREMENTS
 
 <ul>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Bachelor&rsquo;s degree in computer science, Communications Engineering.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;2 to 3 years of experience
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Strong programming skills in languages such as Python.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Proficiency in data modeling techniques and data integration methodologies.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience with ETL tools and data integration frameworks.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Knowledge of relational databases, SQL, and database design principles.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Familiarity with big data technologies and distributed computing frameworks (e.g., Hadoop, Spark).
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Understanding of data warehousing concepts.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Understanding of on-premises and cloud data storage and processing technologies.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience with data processing and manipulation libraries (e.g., pandas, NumPy).
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Familiarity with data governance principles including data quality.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience with data orchestration and scheduling tools like airflow.
 </li>
 <li>
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Very Good
 
 
 </li>
 </ul>
</div>

GB Corp

<div>
 
 Responsible for designing, building, and maintaining robust data pipelines and platforms that enable reliable data flow across the organization. This role focuses on developing scalable and high-performance data solutions, optimizing data processing, and ensuring data availability for analytics and business applications. The Senior Data Engineer will leverage expertise in modern data engineering practices, cloud technologies, and big data platforms to deliver efficient, secure, and well-governed data ecosystems.
 
 
 
 
 
 Data Architecture &amp; Design:
 
 <ul>
 <li>
 Develop and maintain a scalable, secure, and high-performance data architecture aligned with business needs.
 </li>
 <li>
 Ensure seamless data flow between systems, integrating structured and unstructured data sources.
 </li>
 <li>
 Define and implement best practices for data storage, processing, and security.
 </li>
 <li>
 Select and optimize data platforms, tools, and technologies for efficiency and cost-effectiveness.
 </li>
 </ul>
 
 
 
 
 Data Modeling:
 
 <ul>
 <li>
 Design and implement data models (dimensional, relational, Data Vault, NoSQL) to support operational and analytical use cases.
 </li>
 <li>
 Ensure consistency, accuracy, and integrity of data models across the organization.
 </li>
 <li>
 Continuously refine models to improve performance and adaptability to evolving business requirements.
 </li>
 <li>
 Establish and enforce data modeling standards and governance.
 </li>
 </ul>
 
 
 
 
 Data Engineering and Pipeline Development:
 
 <ul>
 <li>
 Build, optimize, and maintain automated ETL/ELT pipelines to process large-scale data.
 </li>
 <li>
 Troubleshoot, debug and upgrade existing ETL solutions.
 </li>
 <li>
 Enhance data infrastructure to support efficient storage, retrieval, and transformation.
 </li>
 <li>
 Implement automation to reduce manual processes and increase workflow efficiency.
 </li>
 <li>
 Ensure data pipelines are robust, scalable, and support real-time and batch processing.
 </li>
 <li>
 Identify data discrepancies and develop data metrics.
 </li>
 </ul>
 
 
 
 
 Innovation &amp; Technology Adoption:
 
 <ul>
 <li>
 Stay up to date with the latest trends in data architecture, engineering, and analytics to identify and implement innovative solutions.
 </li>
 <li>
 Research and integrate cutting-edge tools and platforms to enhance data management capabilities and streamline processes.
 </li>
 <li>
 Encourage a team culture focused on continuous improvement, supporting experimentation with new technologies and methodologies.
 </li>
 <li>
 Develop and execute a technology roadmap to ensure the team is using the best tools available to meet both current and future data needs.
 </li>
 </ul>
 
 
 
 
 Optimization &amp; Performance Management:
 
 <ul>
 <li>
 Define and enforce data governance policies, ensuring compliance with GDPR, and other regulations.
 </li>
 <li>
 Monitor and optimize database performance, query execution, and storage efficiency.
 </li>
 <li>
 Manage data quality, metadata, and lineage to ensure reliability and transparency.
 </li>
 <li>
 Implement proactive monitoring and alerting for data infrastructure health.
 </li>
 <li>
 Monitor performance and quality control plans to identify improvements.
 </li>
 </ul>
 
 
 
 
 Collaboration with Cross-Functional Teams:
 
 <ul>
 <li>
 Work closely with data scientists, business analysts, and BI teams to understand data requirements and design solutions that enable advanced analytics, reporting, and decision-making.
 </li>
 <li>
 Act as a bridge between business units and IT, ensuring that data architecture and engineering solutions meet both technical and business needs.
 </li>
 <li>
 Lead efforts to optimize data workflows and processes across departments, driving efficiency and alignment in data operations.
 </li>
 </ul>
 
 
 
 
 Educational Requirements: Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, Information Systems, or a related field.
 
 
 Advanced degrees provide deeper technical and strategic insights, enabling the professional to drive complex data solutions and innovations at the organizational level.
 
 
 Special Certification or Training Required:
 
 <ul>
 <li>
 Certified Data Management Professional (CDMP) &ndash; Preferred for expertise in data architecture and governance is preferred.
 </li>
 <li>
 Microsoft Certified: Azure Data Engineer Associate or AWS Certified Data Engineer Associate is preferred.
 </li>
 </ul>
 
 Required Industry Experience:
 
 <ul>
 <li>
 3-6 years of experience in Data Engineering, and Data Modeling with a proven track record of leading large-scale enterprise data initiatives.
 </li>
 <li>
 Expertise in designing, implementing, and optimizing complex data ecosystems in hybrid environments.
 </li>
 <li>
 Strong background in data governance, security, compliance, and risk management across enterprise systems.
 </li>
 <li>
 Hands-on experience managing data integration, migration, and transformation projects in a large-scale business setting.
 </li>
 </ul>
 
 
 
 
 Technological Requirements:
 
 <ul>
 <li>
 Deep expertise in architecting, optimizing, and managing both relational (e.g., Oracle, PostgreSQL) and NoSQL (e.g., MongoDB, Cassandra) databases.
 </li>
 <li>
 Proven track record of designing and implementing scalable, enterprise-level Data Warehouse (DWH) architectures.
 </li>
 <li>
 Expert-level proficiency in writing and tuning complex SQL queries, stored procedures, functions, and triggers for high-performance data processing.
 </li>
 <li>
 Strong analytical skills related to structured or unstructured data sets.
 </li>
 <li>
 Advanced expertise in data modeling techniques, including Data Vault, Dimensional Modeling, and Entity-Relationship Modeling.
 </li>
 <li>
 Extensive experience in building and maintaining robust, scalable data pipelines (ETL/ELT) using modern technologies
 </li>
 <li>
 Expert programming skills in Python and SQL for data engineering and automation tasks, along with a strong understanding of version control (Git)
 </li>
 <li>
 Proven expertise in architecting and managing data lakes and data warehouses for big data environments.
 </li>
 </ul>
 
 
 
 
 Language Requirements: Fluent in English.
 
 
 
</div>

Senior Data Engineer

Systems Limited - Egypt

<div>
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Build and maintain data warehouse and data marts, including ODS and internal departmental marts.
 </li>
 <li>
 Gather, process, maintain, and analyze large datasets, ensuring data accuracy and quality.
 </li>
 <li>
 Design, automate, and support ETL pipelines and data flows across multiple applications.
 </li>
 <li>
 Create logical and physical data flow models and mapping designs for ETL processes.
 </li>
 <li>
 Strong SQL skills (performance tuning, index management) and solid understanding of database structures.
 </li>
 <li>
 Strong understanding of data modeling concepts.
 </li>
 <li>
 Familiarity with SQL and NoSQL storage, and Big Data technologies (Hive, Impala, YARN, Kafka, etc.).
 </li>
 </ul>
 
 
 
 
 Informatica-specific requirements:
 
 
 <ul>
 <li>
 Hands-on experience with Informatica PowerCenter development (mappings, sessions, workflows).
 </li>
 <li>
 Strong knowledge of Informatica transformations (e.g., Lookup, Joiner, Aggregator, Expression, Router, Sorter) and performance tuning.
 </li>
 <li>
 Experience with Informatica Developer.
 </li>
 <li>
 Experience with Informatica B2B is a plus.
 </li>
 <li>
 Ability to design, automate, monitor, and troubleshoot ETL jobs, including scheduling.
 </li>
 </ul>
 
 
 
 
 Banking sector requirements (preferred):
 
 
 <ul>
 <li>
 Previous experience in the banking sector, preferably business banking, including working with banking datasets.
 </li>
 <li>
 Strong understanding of data quality and reconciliation expectations in banking environments.
 </li>
 <li>
 Experience working in regulated environments and change control practices is a strong plus.
 </li>
 </ul>
 
 
</div>

Muller's Solutions

<div>M&uuml;ller&rsquo;s Solutions is looking for an experienced Big Data Engineer to join our innovative team. In this role, you will be responsible for designing and developing scalable big data solutions that enable advanced analytics and insights across the organization. You will work with large data sets and utilize cutting-edge technologies to ensure data processing is efficient and reliable.
Key Responsibilities:<ul>
<li>Design, build, and maintain scalable data pipelines using big data technologies such as Apache Spark, Hadoop, and Kafka.</li>
<li>Collaborate with data scientists, analysts, and IT teams to identify data requirements and deliver solutions that meet business needs.</li>
<li>Ensure high data quality and integrity by implementing robust data validation and testing processes.</li>
<li>Optimize data storage solutions for performance and cost-efficiency across cloud and on-premises environments.</li>
<li>Monitor and troubleshoot data processing workflows to ensure timely data delivery.</li>
<li>Document data architectures, processes, and workflows for knowledge sharing and compliance.</li>
<li>Stay ahead of industry trends and best practices in big data technologies and methodologies.</li> 
</ul> 
 
Requirements 
Requirements:<ul>
<li>Bachelor's degree in Computer Science, Information Technology, or a related field.</li>
<li>3+ years of experience as a Big Data Engineer or in a similar data engineering role.</li>
<li>Proficiency in big data technologies such as Apache Spark, Hadoop, and Apache Kafka.</li>
<li>Strong coding skills in programming languages like Java, Scala, or Python.</li>
<li>Familiarity with data processing frameworks and ETL tools.</li>
<li>Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and data storage solutions (e.g., HDFS, S3, BigQuery).</li>
<li>Analytical mindset and excellent problem-solving abilities.</li>
<li>Strong communication skills to collaborate effectively with technical and non-technical stakeholders.</li>
<li>A self-motivated and proactive approach to work, with the ability to manage multiple tasks and deadlines.</li>
</ul>Preferred Qualifications:<ul>
<li>Experience with machine learning frameworks and algorithms is a plus.</li>
<li>Knowledge of data governance and security best practices.</li>
<li>Familiarity with containerization technologies and orchestration tools like Docker and Kubernetes.</li> 
</ul> 
 
Benefits 
1- Attractive Package.
2- Family Benefits.
3- Visa.
4-Air Tickets.</div>

Big Data Engineer

Explore 1622+ Data engineer in Egypt this March. Find roles across top companies and apply now to boost your career.

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