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Müller's Solutions

<div>
 M&uuml;ller's Solutions is actively searching for a Google Cloud Data Engineer to enhance our data processing capabilities. In this vital role, you will be responsible for designing and implementing data pipelines leveraging Google Cloud technologies. You will work closely with data analysts, business stakeholders, and other engineering teams to ensure data is accurately processed, integrated, and made available for analysis and reporting.
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Design, develop, and optimize data pipelines using Google Cloud Dataflow, Pub/Sub, and other GCP data services
 </li>
 <li>
 Implement data lakes and data warehouses using Google BigQuery, ensuring efficient data storage, retrieval, and processing
 </li>
 <li>
 Collaborate with data scientists and analysts to understand data requirements and provide solutions that meet business needs
 </li>
 <li>
 Monitor and evaluate data pipeline performance, implementing necessary optimizations and troubleshooting issues as they arise
 </li>
 <li>
 Ensure data quality by developing and implementing validation routines and data profiling techniques
 </li>
 <li>
 Document data architecture, ETL processes, and operational procedures to facilitate knowledge sharing within the team
 </li>
 <li>
 Stay informed of emerging trends and best practices in data engineering and GCP technologies
 </li>
 <li>
 Participate in team efforts to define and enhance data governance and management practices
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 Requirements:
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field
 </li>
 <li>
 3+ years of experience in data engineering, with a focus on Google Cloud Platform
 </li>
 <li>
 Proficient in designing and implementing data pipelines using Google Cloud Dataflow, BigQuery, and related tools
 </li>
 <li>
 Strong SQL skills and experience in data modeling and data warehousing concepts
 </li>
 <li>
 Familiarity with programming languages such as Python or Java for data processing tasks
 </li>
 <li>
 Ability to work with various data sources, including structured and unstructured data
 </li>
 <li>
 Strong analytical and problem-solving skills with attention to detail
 </li>
 <li>
 Ability to effectively communicate technical concepts to both technical and non-technical stakeholders
 
 
 </li>
 </ul>
 
 Preferred Qualifications:
 
 
 
 <ul>
 <li>
 Google Cloud certifications (e.g., Google Cloud Professional Data Engineer) are highly desirable
 </li>
 <li>
 Experience with real-time data processing using Apache Beam and Google Cloud Pub/Sub
 </li>
 <li>
 Understanding of CI/CD practices in data engineering workflows
 </li>
 <li>
 Knowledge of data visualization tools and techniques to present data insights effectively
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 1- Attractive Package.
 
 
 2- Family Benefits.
 
 
 3- Visa.
 
 
 4-Air Tickets.
</div>

Google Cloud Data Engineer

almentor

<div>
 
 
 About almentor
 
 : almentor is a cutting-edge online video marketplace for e-learning and professional business development throughout the Middle East and Africa. Offering video courses in Arabic and English, we curate top-rated training programs of expert-created content and guided curriculum with interactive delivery.
 
 
 
 
 
 
 Our Mission:
 
 🚀 almentor is on a mission to increase accessibility to affordable quality education for Arabic-speaking communities and a Goal to serve 10 million learners in MENA
 
 
 
 
 
 
 Job Overview:
 
 
 
 Reporting to the Head of Engineering, your role is to design, build, and operate the data and applied AI foundations that power intelligent learning experiences and business workflows. You will ship production- grade pipelines, retrieval/search systems, and LLM-enabled features that are measurable, secure, and reliable.
 
 
 
 
 
 We are committed to building software that is not only functional and reliable, but also beautiful and intuitive. Our engineers and designers work together to create products that are a joy to use, and that solve real-world problems in innovative ways. We believe in the Agile and XP methodologies, and we prioritize collaboration, communication, and continuous improvement in everything we do.
 
 
 
 
 
 We are embarking on an exciting journey of rebuilding our product and engineering organization to drive innovation and growth. Our goal is to create a world-class platform that delivers the best possible learning experiences to our users.
 
 
 Share the journey along with engineers, product managers, and leaders from the most successful organizations in the region.
 
 
 
 
 
 
 As a Senior Data / AI Engineer, your'll spend your time on:
 
 
 <ul>
 <li>
 Blending data engineering, applied AI implementation, and operational ownership.
 </li>
 <li>
 Architect, implement, and maintain pipelines that ingest, transform, and serve data for product features, analytics, and AI workflows.
 </li>
 <li>
 Build indexing and retrieval layers (structured + unstructured) to power search, recommendations, and AI assistants (RAG).
 </li>
 <li>
 Implement LLM-powered features: prompt orchestration, tool/function calling, RAG patterns, structured extraction, summarization.
 </li>
 <li>
 Add guardrails: policy checks, rate limits, cost controls, and safe handling of sensitive data.
 </li>
 <li>
 Create evaluation harnesses and regression tests for retrieval of quality and AI outputs (offline datasets + automated checks).
 </li>
 <li>
 Instrument pipelines/services with logging, tracing, metrics, and data quality monitoring.
 </li>
 <li>
 Partner closely with product managers, designers, and engineers to translate user needs into measurable data/AI capabilities.
 </li>
 <li>
 Participate in sprint planning, refinement, and cross-team alignment to keep execution predictable.
 </li>
 <li>
 Own your pipelines and services in production &mdash; incident response, post-mortems, runbooks, and continuous improvement.
 </li>
 <li>
 Optimize latency, cost, and throughput across data processing, indexing, and AI inference usage.
 </li>
 <li>
 A typical day might look like: checking pipeline freshness and alerts in the morning, tuning chunking/index mappings for a new course search mid-day, pairing with product on evaluation metrics for an AI study
 </li>
 <li>
 Assistant in the afternoon, and ending the day by shipping a monitored RAG endpoint with cost budgets and regression tests.
 </li>
 </ul>
 
 
 Role Objectives
 
 
 <ul>
 <li>
 Design, oversee, build and operate data pipelines and applied AI systems that power our education platform across consumer and business customer segments.
 </li>
 <li>
 Build and scale retrieval and search foundations (hybrid search, metadata filtering, vector retrieval) that enable AI experiences.
 </li>
 <li>
 Deliver production LLM capabilities with measurable quality, cost controls, and safety guardrails.
 </li>
 <li>
 Improve system performance, reliability, observability, and maintainability through proactive monitoring and data quality checks.
 </li>
 <li>
 Collaborate closely with stakeholders (product managers, designers, frontend/mobile engineers) to translate business requirements into technical solutions.
 </li>
 <li>
 Contribute to sprint planning, technical documentation, and cross-team initiatives as a senior engineering voice.
 </li>
 <li>
 Contributing to sprint planning, technical documentation, and cross-team initiatives as a senior voice in the engineering org.
 </li>
 </ul>
 
 
 
 
 
 The ideal candidate will have:
 
 
 <ul>
 <li>
 4+ years of experience in data engineering, backend engineering, or platform engineering, with meaningful production ownership.
 </li>
 <li>
 Strong SQL and data modeling skills; experience designing schemas and data contracts.
 </li>
 <li>
 Experience building and operating pipelines (batch and/or streaming), including backfills and data quality validation.
 </li>
 <li>
 Experience with search/indexing systems and retrieval patterns (e.g., OpenSearch/Elasticsearch, vector DBs, hybrid search).
 </li>
 <li>
 Hands-on experience implementing LLM-powered features (RAG, tool/function calling, prompt/version management) &mdash; no deep ML required.
 </li>
 <li>
 Familiarity with CI/CD, containerization (Docker), and cloud services (ex. AWS, GCP).
 </li>
 <li>
 Strong problem-solving and debugging skills, with a proactive attitude towards owning and improving systems.
 </li>
 <li>
 Strong written and verbal communication skills, with the ability to explain complex ideas clearly to technical and non-technical stakeholders.
 </li>
 <li>
 Bachelor&rsquo;s degree in computer science, Engineering, or a related field is preferred but not required
 </li>
 </ul>
</div>

Senior Data & Applied AI Engineer

Modupay

<div>
 
 Job Purpose:
 
 
 Design, build, and maintain scalable data pipelines and infrastructure to support Modupay's intelligence and insights products. Ensure data reliability, availability, and quality across the organization, with a focus on supporting payments and fintech-related data needs.
 
 
 
 
 
 Key Accountabilities:
 
 <ul>
 <li>
 Develop, and maintain robust data pipelines that ingest, transform, and normalize large volumes of transaction data from multiple sources
 </li>
 <li>
 Implement incremental loading, error handling, retry logic, and pipeline monitoring to ensure SLA-driven data freshness for downstream commercial products.
 </li>
 <li>
 Build unified data models that normalize transaction data across payment schemes and local rails into consistent reporting structures, enabling cross-market and cross-product analytics.
 </li>
 <li>
 Implement data quality, validation, and testing frameworks (data contracts, automated checks, anomaly detection) to ensure integrity of data flowing into analytics products, reporting, and machine learning use cases.
 </li>
 <li>
 Ensure data quality, integrity, and consistency through monitoring, validation, and testing frameworks.
 </li>
 <li>
 Collaborate with data analysts and internal stakeholders to understand data requirements and deliver scalable solutions.
 </li>
 <li>
 Implement and maintain data governance, security, and privacy best practices in compliance with Modupay's policies and regulatory requirements.
 </li>
 <li>
 Identify performance bottlenecks and optimize query performance, data storage, and processing efficiency.
 </li>
 <li>
 Stay current with emerging technologies and industry trends, recommending improvements to the data architecture and tooling
 </li>
 </ul>
 
 
 
 
 Knowledge and Competencies:
 
 
 
 
 
 Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field. Master's degree is a plus.
 
 <ul>
 <li>
 Advanced SQL proficiency. Experience with PostgreSQL and Oracle preferred.
 </li>
 <li>
 3 years of experience in data engineering preferably within payments, fintech, or financial services.
 </li>
 <li>
 Strong data modeling skills
 </li>
 <li>
 Hands-on experience with ETL/ELT frameworks and tools
 </li>
 <li>
 Proficiency in Python or another data engineering language for pipeline development, scripting, and automation.
 </li>
 <li>
 Experience with data quality and testing frameworks
 </li>
 <li>
 Exposure to cloud data platforms (AWS, GCP, or Azure)
 </li>
 <li>
 Experience with BI/visualization tool integration
 </li>
 <li>
 Strong analytical and problem-solving skills with attention to data accuracy and reconciliation.
 </li>
 <li>
 Effective communicator, able to translate technical data architecture decisions into business-understandable terms for analysts and product stakeholders.
 </li>
 <li>
 Fluency In English
 </li>
 </ul>
 
 
</div>

Senior Data Engineer

<div>
 M&uuml;ller'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

Coca-Cola HBC

<div>
 
 
 Department
 
 : Data, Insights &amp; AI
 
 
 
 Location
 
 : Egypt (Cairo)
 
 
 
 
 
 We are expanding our team and seeking a highly skilled Data Engineer with strong expertise in Microsoft Azure, solid knowledge of machine learning, experience with modern software delivery practices, and a curious mindset toward artificial intelligence applications to join our Analytics Engineering team within the Digital &amp; Technology Platform Services (DTPS) organization at Coca‑Cola Hellenic. In this role, you will contribute to shaping the strategy, design, and development of advanced analytics solutions that deliver meaningful insights and support data‑driven decision‑making across the business. You will be part of the Data Insights and Artificial Intelligence (DIAI) team, integrating and transforming data into scalable, analytics‑ready solutions and cutting‑edge machine learning applications.
 
 
 
 
 
 
 
 
 
 YOUR NEW KEY RESPONSIBILITIES:
 
 
 
 &bull; Design, develop, implement, and optimize scalable, high performance, secure, and cost-efficient data pipelines using Microsoft Azure cloud services and large scale data technologies, including Apache Spark and PySpark built with object-oriented programming principles.
 
 
 &bull; Load and process data from Azure Data Lake, orchestrate Azure Databricks jobs, and manage Azure Data Factory pipelines with a high degree of proficiency.
 
 
 &bull; Develop and implement robust data quality frameworks to ensure data integrity across all stages of the data lifecycle.
 
 
 &bull; Perform data profiling, analysis, and validation to identify, troubleshoot, and resolve data quality issues in a timely and effective manner.
 
 
 &bull; Implement security, governance, and access control measures to safeguard sensitive data within Microsoft Azure environments.
 
 
 &bull; Build and maintain machine learning workflows and data pipelines that support model development, deployment, and ongoing monitoring.
 
 
 &bull; Utilize Git based version control to manage code repositories, apply structured branching strategies, and enable collaborative development practices.
 
 
 &bull; Apply Agile methodologies to plan, prioritize, and deliver data engineering work in iterative development cycles.
 
 
 &bull; Develop and maintain comprehensive documentation for data solutions, including data models, data flows, architectural diagrams, and detailed technical specifications.
 
 
 &bull; Stay up to date with Microsoft Azure data services, large scale data tools, DevOps practices, and broader industry best practices, providing recommendations for adoption and continuous improvement.
 
 
 &bull; Collaborate with Azure developers and data engineers from Coca Cola Hellenic vendors, offering guidance on data engineering techniques, standards, and methodologies.
 
 
 &bull; Work closely with DevOps teams to implement and maintain continuous integration and continuous delivery pipelines for Azure based applications and data workflows.
 
 
 &bull; Support Microsoft Power Business Intelligence developers by evaluating and optimizing data connection methods and data transfer strategies, ensuring high performance, scalability, data quality, and security.
 
 
 
 
 
 
 ARE THESE YOUR SECRET INGREDIENTS?
 
 
 
 &bull; Bachelor&rsquo;s degree in computer science, engineering, or a related discipline (or equivalent practical experience),
 
 
 &bull; Two or more years of professional experience; Microsoft Azure Data Engineer certification is considered an advantage.
 
 
 &bull; Strong understanding of secure software development and modern software delivery practices, including continuous integration, continuous delivery, automated testing, automated deployments, and extensive experience using Git for version control
 
 
 &bull; Deep expertise with Microsoft Azure data services, including Azure Data Factory, Azure Data Lake Storage, and Azure Databricks, with solid experience applying performance optimization techniques for analytics and reporting workloads.
 
 
 &bull; Strong hands-on experience with Apache Spark and PySpark using object-oriented programming, along with strong skills in Python and SQL to design and optimize scalable data pipelines across largescale data architectures that handle big data.
 
 
 &bull; Knowledge of Systems, Applications, and Products Business Warehouse extractors, transformations, and data export processes, along with experience working within Agile and Scaled Agile Framework environments.
 
 
 &bull; Proven ability to ensure data quality, reliability, and operational efficiency, supporting advanced analytics and machine learning workflows.
 
 
 &bull; A foundational understanding of machine learning concepts, feature engineering, and machine learning operations for model deployment and monitoring.
 
 
 
 
 
 
 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 &ndash; for us and for you &ndash; 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>

Data Engineer

NorthBay - Pakistan

<div>
 
 Experience:
 
 5&ndash;7 Years
 
 
 
 Location:
 
 Cairo, Egypt (Onsite)
 
 
 
 Employment Type:
 
 Full-Time
 
 
 
 Position Overview
 
 
 
 We are looking for a skilled Senior Data Engineer with strong AWS expertise to design, develop, and optimize cloud-based data pipelines and solutions. The role involves hands-on development, collaboration with cross-functional teams, and contributing to scalable, high-performance data platforms. The ideal candidate has solid AWS experience, strong programming skills, and an understanding of data engineering best practices.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Develop and maintain batch and real-time data pipelines on AWS
 </li>
 <li>
 Implement ETL/ELT solutions using AWS Glue, Spark on EMR, and other AWS services
 </li>
 <li>
 Assist in workflow orchestration using Apache Airflow (MWAA)
 </li>
 <li>
 Support serverless data processing using AWS Lambda
 </li>
 <li>
 Participate in designing data warehousing solutions using Amazon Redshift
 </li>
 <li>
 Design and manage data storage strategies with Amazon S3 and DynamoDB
 </li>
 <li>
 Apply data governance and access controls using AWS DataZone
 </li>
 <li>
 Monitor and troubleshoot data platform issues using Amazon CloudWatch
 </li>
 <li>
 Collaborate with Analytics, BI, Data Science, and Business teams
 </li>
 <li>
 Write clean, efficient code, and perform peer code reviews
 </li>
 <li>
 Follow security, compliance, and data governance standards
 
 
 </li>
 </ul>
 
 Required Skills &amp; Experience
 
 
 
 <ul>
 <li>
 5&ndash;7 years of experience in Data Engineering or related roles
 </li>
 <li>
 3+ years of hands-on experience designing data solutions on AWS
 </li>
 <li>
 Proficiency with: AWS Glue, Amazon EMR (Spark), AWS Lambda, Apache Airflow (MWAA), Amazon EC2, Amazon CloudWatch, Amazon Redshift, Amazon DynamoDB, AWS DataZone, Amazon S3
 </li>
 <li>
 Strong programming skills in Python
 </li>
 <li>
 Advanced SQL skills with performance tuning expertise
 </li>
 <li>
 Understanding of data warehousing, data modeling (Star/Snowflake), ETL/ELT best practices
 </li>
 <li>
 Familiarity with Agile/Scrum delivery environments
 </li>
 <li>
 Problem-solving and analytical skills
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 AWS Professional Certification (Solutions Architect / Data Analytics Specialty)
 </li>
 <li>
 Experience with real-time streaming (Kinesis, Kafka)
 </li>
 <li>
 Exposure to data governance and metadata management tools
 </li>
 <li>
 Knowledge of cost optimization in AWS
 </li>
 </ul>
</div>

Senior Data Engineer – AWS

Accenture

<div>
 
 Overview:
 
 
 
 As an Oracle Data Conversion Lead at Accenture, you will play a pivotal role in designing, developing, and maintaining robust data solutions to support data generation, collection, and processing. Your responsibilities will include creating and optimizing data pipelines, ensuring data quality, and implementing ETL processes to facilitate seamless data migration and deployment across systems.
 
 
 You will act as a subject matter expert in Oracle Data Integrator (ODI) and Data Migrations, leveraging your expertise to guide and manage teams effectively. You will be responsible for driving team decisions, collaborating with multiple teams, and contributing to strategic initiatives while delivering innovative solutions to complex challenges.
 
 
 
 Key Responsibilities:
 
 
 
 
 <li>
 Lead the design and implementation of data solutions that enhance operational efficiency and scalability.
 
 </li>
 <li>
 Collaborate with cross-functional teams to identify data requirements and deliver effective solutions.
 
 </li>
 <li>
 Develop and optimize data pipelines to ensure performance, reliability, and scalability.
 
 </li>
 <li>
 Conduct regular assessments of data quality and implement improvements to maintain high standards.
 
 </li>
 <li>
 Stay abreast of industry trends, emerging technologies, and best practices in data engineering and Oracle Data Integration.
 
 </li>
 <li>
 Provide mentorship and guidance to team members, fostering a culture of collaboration and continuous improvement.
 
 </li>
 <li>
 Master proficiency in Oracle Data Integrator (ODI).
 
 </li>
 <li>
 Expert proficiency in Data Migrations, Data Engineering, Data Pipelines, and Data Processing.
 
 </li>
 <li>
 Strong problem-solving skills with the ability to provide solutions across multiple teams.
 
 </li>
 <li>
 Excellent communication and leadership skills to manage and collaborate effectively with diverse teams.
 
 
 
 </li>
</div>

Oracle Data Conversion Lead - Associate Manager

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