analytics engineer

Orange Business

<div>
 
 About Us
 
 
 
 Join us at Orange Business!
 
 
 We are a network and digital integrator that understands the entire value chain of the digital world, freeing our customers to focus on the strategic initiatives that shape their business.
 
 
 Every day, you will collaborate with a team dedicated to providing consistent, sustainable global solutions, no matter where our customers operate. With over 30,000 employees across Asia, the Americas, Africa, and Europe, we offer a dynamic environment to develop and perfect your skills in a field filled with exciting challenges and opportunities.
 
 
 
 About The Role
 
 
 
 <ul>
 <li>
 Translate reporting and analytics needs into scalable data models (star/snowflake), conformed dimensions, and data marts.
 </li>
 <li>
 Evolve the data warehouse architecture and schema design to support new use cases and performance goals.
 </li>
 <li>
 Build and maintain ETL/ELT pipelines in Python/SQL; orchestrate workflows and enforce data quality checks.
 </li>
 <li>
 Implement a semantic/metrics layer to support consistent KPIs and enable self-service analytics.
 </li>
 <li>
 Define and run data quality tests, anomaly detection, lineage, and documentation to improve trust in data.
 </li>
 <li>
 Integrate diverse data sources (operational systems, relational DBs, Elasticsearch, APIs, message queues).
 </li>
 <li>
 Optimize performance (partitioning, indexing, clustering, materialized views) for reporting and ad-hoc analysis.
 </li>
 <li>
 Maintain security, confidentiality, and integrity of data in line with relevant regulations; implement RBAC and data masking where appropriate.
 </li>
 <li>
 Partner with analysts to design dashboards and reporting assets; enable BI best practices and governance.
 </li>
 <li>
 Participate in the on-call rotation to ensure data pipelines and services remain reliable.
 
 
 </li>
 </ul>
 
 About You
 
 
 
 <ul>
 <li>
 Advanced SQL and data modeling skills (dimensional modeling, SCDs, normalization vs. denormalization).
 </li>
 <li>
 Strong Python for data processing (e.g., pandas, SQLAlchemy) and building ETL/ELT with automated testing.
 </li>
 <li>
 Experience with CI/CD for data (Git, code reviews, data tests using dbt/Great Expectations or similar).
 </li>
 <li>
 Experience with at least one of: PostgreSQL, MySQL/MariaDB, or Elasticsearch.
 </li>
 <li>
 Orchestration and transformation tools (e.g., Airflow/Prefect and/or dbt).
 </li>
 <li>
 Comfortable with Linux, Docker, and Git.
 </li>
 <li>
 BI/visualization experience (e.g., Power BI, Tableau, Looker, Superset, or Metabase) and dashboard design fundamentals.
 </li>
 <li>
 Writing tests gives you confidence in your code.
 </li>
 <li>
 Willingness to work in an on-call rotation.
 </li>
 <li>
 Full professional proficiency in English (written and verbal ) essential
 </li>
 <li>
 4+ years of relevant experience.
 
 
 </li>
 </ul>
 
 Plus:
 
 
 
 <ul>
 <li>
 Experience with message queues and streaming (RabbitMQ, Kafka).
 </li>
 <li>
 Exposure to modern cloud warehouses (Snowflake, BigQuery, Redshift) or columnar/time-series stores (ClickHouse, TimescaleDB).
 </li>
 <li>
 Experience with Kubernetes for deploying data workloads.
 </li>
 <li>
 Data catalog/lineage tooling (DataHub, OpenLineage, Amundsen) and metrics layer design (dbt metrics, LookML, semantic layers).
 </li>
 <li>
 Security telemetry analytics experience and governance for sensitive data (RBAC, masking, GDPR).
 
 
 </li>
 </ul>
 You bring a can-do attitude, tackle challenges head-on and challenge the status quo with new and innovative ideas.
 
 
 
 What We Offer
 
 
 
 <ul>
 <li>
 Global Opportunities: Work in multi-national teams with opportunity to collaborate with colleagues and customers from all over the world.
 </li>
 <li>
 Flexible Work Environment: Flexible working hours and possibility to combine work from office and home (hybrid ways of working).
 </li>
 <li>
 Professional Development: training programs and upskilling/re-skilling opportunities.
 </li>
 <li>
 Career Growth: Internal growth and mobility opportunities within Orange.
 </li>
 <li>
 Caring and Daring Culture: Health and well-being programs and benefits, diversity &amp; inclusion initiatives, CSR and employee connect events.
 </li>
 <li>
 Reward Programs: Employee Referral Program, Change Maker Awards.
 
 
 </li>
 </ul>
 
 Only Your Skills Matter
 
 
 
 Regardless of your age, gender identity, race, ethnic origin, religion/belief, sexual orientation, marital status, neurotype, disability, veteran status or appearance, we encourage diversity within our teams because it is a strength for the collective and a vector of innovation. Orange Group is a disabled-friendly company and equal opportunity employer: don't hesitate to tell us about your specific needs.
</div>

Analytics Engineer

Mondia

<div>
 We are seeking a highly skilled and detail-oriented
 
 Digital Analytics Implementation Specialist
 
 to join our team. This role focuses on the technical implementation, maintenance, and debugging of tracking and analytics tools to ensure seamless data collection, integration, and analysis across web and mobile platforms. You will collaborate with cross-functional teams to enable efficient tracking, accurate reporting, and actionable insights, leveraging tools like Clevertap, Appsflyer, Adjust, Mixpanel, and GA4, along with Amazon Redshift and QuickSight for advanced analytics.
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Data Layer Implementation:
 </li>
 <ul>
 <li>
 Design, implement, and maintain data layers across websites and mobile applications in compliance with business and technical requirements
 </li>
 <li>
 Enable seamless integration with analytics and marketing tools, such as Clevertap, Appsflyer, Adjust, Mixpanel, and Google Analytics 4 (GA4)
 </li>
 <li>
 Work closely with developers to integrate custom events, user properties, and other tracking mechanisms
 </li>
 </ul>
 <li>
 Technical Implementation:
 </li>
 <ul>
 <li>
 Support tech team with configuration and deployment for tools like Appsflyer, Adjust, and Clevertap data layer implementations within mobile applications and
 </li>
 <li>
 Manage analytics tools such as Mixpanel and GA4 to track and analyze user behaviors and performance metrics and integration of tools like Google Ads or Google search console
 </li>
 <li>
 Support tech team to integrate data from various data sources to Amazon Redshift for centralized data storage and perform data extraction for reporting
 </li>
 <li>
 Build and optimize dashboards in Amazon QuickSight to deliver actionable business insights
 </li>
 </ul>
 <li>
 Debugging and Troubleshooting:
 </li>
 <ul>
 <li>
 Utilize debugging tools like Chrome Developer Tools, Charles Proxy, Android studio or Fiddler to troubleshoot data inconsistencies and ensure tags fire correctly
 </li>
 <li>
 Audit and resolve issues related to SDK implementations, data layer structure, and third-party tracking integrations
 </li>
 <li>
 Ensure cross-platform data integrity and troubleshoot discrepancies in real-time and historical analytics
 </li>
 </ul>
 <li>
 Testing and Validation:
 </li>
 <ul>
 <li>
 Conduct end-to-end testing of implementations to ensure data accuracy across multiple devices, browsers, and environments
 </li>
 <li>
 Validate the integration of tracking tools and ensure compliance with data privacy regulations such as GDPR and CCPA
 </li>
 </ul>
 <li>
 Documentation and Reporting:
 </li>
 <ul>
 <li>
 Maintain detailed documentation of data layer specifications, SDK implementations, and debugging processes
 </li>
 <li>
 Create technical reports and dashboards to monitor tracking performance and data quality
 </li>
 <li>
 Collaborate with analytics and BI teams to design scalable reporting solutions
 
 
 </li>
 </ul>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelor's degree in computer science, Information Systems, or a related field
 </li>
 <li>
 Proven experience in implementing and debugging data layers and analytics tools
 </li>
 <li>
 Proficiency in tools like Clevertap, Appsflyer, Adjust, Mixpanel, and Google Analytics 4 (GA4)
 </li>
 <li>
 Strong knowledge of tag management systems (e.g., GTM, Tealium, Adobe Launch)
 </li>
 <li>
 Proficiency in JavaScript, HTML, and CSS for tracking code customization is must
 </li>
 <li>
 Familiarity with debugging tools such as Charles Proxy, Android studio, Browser DevTools, or Fiddler
 </li>
 <li>
 Hands-on experience with Amazon Redshift for data management and QuickSight for reporting
 </li>
 <li>
 Strong problem-solving skills and attention to detail
 </li>
 <li>
 Understanding of data security and compliance frameworks (e.g., GDPR, CCPA)
 
 
 </li>
 </ul>
 
 Preferred Qualifications:
 
 
 
 <ul>
 <li>
 Experience with server-side tagging and cloud-based data collection methods
 </li>
 <li>
 Knowledge of API integrations and data pipeline management
 </li>
 <li>
 Familiarity with ETL processes and data transformation techniques
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Social insurance
 </li>
 <li>
 Health insurance for employee and family
 </li>
 <li>
 The company will contribute up to EUR 25 per month towards staff perks
 </li>
 <li>
 Benefit from our performance-based bonus scheme, in line with company policy.
 </li>
 <li>
 EUR equivalent salaries paid in EGP
 </li>
 </ul>
</div>

Digital Analytics Specialist

Coca-Cola HBC

<div>
 
 
 Department:
 
 Data, Insights &amp; Artificial Intelligence (DIAI)
 
 
 
 Location:
 
 Egypt
 
 
 
 
 
 As a Data Quality Engineer, 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, combined with full ownership of deliverables from design to production support and the flexibility to handle ad-hoc requests and parallel priorities while translating business requirements into scalable and automated data quality solutions.
 
 
 
 
 
 
 YOUR NEW KEY RESPONSIBILITIES
 
 
 
 
 Data Quality Controls (DCC)
 
 
 
 &bull; Build, configure and maintain Data Quality controls in the Data Control Center (DCC).
 
 
 &bull; Translate business requirements into data quality rules, including logic definition, thresholds, exception handling and reduction of false positives.
 
 
 &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, 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 / 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
 
 
 
 
 
 
 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>

Data Engineer

Valeo

<div>
 Responsibilities Cross-Disciplinary Automation
 
 :
 
 Design and implement AI workflows that bridge the gap between Systems Engineering and downstream disciplines (HW, SW, Mech) to ensure seamless requirements traceability and consistency.
 
 
 Physics-Informed Modeling: Develop and deploy Physics-Informed Machine Learning (PIML) models to accelerate simulations in Mechanics and Electrotechnique.
 
 
 
 AI-Enhanced System Engineering
 
 : Integrate AI-assisted coding, automated unit testing, and bug prediction tools into the software development pipeline in compliance with ASPICE standards.
 
 
 
 Predictive Project Management
 
 : Build predictive analytics dashboards for Technical Project Managers to forecast resource bottlenecks, budget risks, and milestone delays using historical project data.
 
 
 
 Standards &amp; Compliance:
 
 Ensure all AI-automated processes and generated outputs adhere to ISO 26262 (Functional Safety) and ISO/SAE 21434 (Cybersecurity) requirements.
 
 
 
 Toolchain Integration
 
 : Lead the integration of AI agents with existing toolchains, including PLM, ALM (Codebeamer), and MATLAB/Simulink.
 
 
 Key competencies
 
 Technical Skills
 
 
 
 AI and Machine Learning
 
 
 <ul>
 <li>
 Generative AI &amp; LLMs
 </li>
 <li>
 Predictive Modeling
 </li>
 <li>
 Computer Vision
 
 
 </li>
 </ul>
 Data Engineering and Management
 
 
 <ul>
 <li>
 Data Pipeline Construction: Automating the flow of data into AI models.
 </li>
 <li>
 Data Quality Assurance: Cleaning and labeling datasets to ensure the AI isn't learning from "noise."
 
 
 </li>
 </ul>
 
 Process Automation &amp; Integration (MLOps)
 
 
 
 <ul>
 <li>
 Workflow Orchestration: Using tools to connect AI outputs to other R&amp;D software (like ELNs or LIMS).
 </li>
 <li>
 Deployment: Ensuring the AI tools are accessible via user-friendly interfaces.
 
 
 </li>
 </ul>
 
 Programming &amp; Scripting
 
 
 
 <ul>
 <li>
 Python
 </li>
 <li>
 Javascript / Google Apps Script
 </li>
 <li>
 Google Docs / Sheets functions &amp; automation
 </li>
 <li>
 HTTP rest API's
 
 
 </li>
 </ul>
 Tooling &amp; ALM: ( Plus Knowledge)
 
 
 <ul>
 <li>
 Codebeamer (Requirement Management Tool)
 </li>
 <li>
 Google Cloud Platform
 
 
 </li>
 </ul>
 Automation &amp; Integration concepts
 
 
 <ul>
 <li>
 AI &amp; Data Handling:
 </li>
 <li>
 Basic to intermediate experience with AI tools, APIs, or AI agents
 </li>
 <li>
 Interest in applying AI to engineering processes
 
 
 </li>
 </ul>
 Soft Skills
 
 
 <ul>
 <li>
 Strong communication and collaboration skills, including ability to translate technical AI capabilities into tangible benefits for the teams
 </li>
 <li>
 Ability to work autonomously and proactively
 </li>
 <li>
 Analytical mindset with strong problem-solving skills
 </li>
 <li>
 User-oriented mindset (training, support, feedback handling)
 </li>
 <li>
 Time Managment
 
 
 </li>
 </ul>
 Nice to Have
 
 
 Experience with requirement traceability or compliance activities
 
 
 Exposure to AI-assisted automation or low-code/no-code platforms
 
 
 Physics-Informed Machine Learning (PIML)
 
 
 Predictive Project Analytics
 
 
 Understanding of system engineering lifecycle and deliverables
 
 
 
 Aware About Automotive Industry And Embedded Systems.
 
 
 
 Years of Experience 2 to 3 years experience in AI &amp; tools development
</div>

AI & Automation Engineer, LIGHT

<div>
 Valeo est une entreprise mondiale de haute technologie qui con&ccedil;oit des solutions r&eacute;volutionnaires pour r&eacute;inventer la mobilit&eacute;. Nous sommes un &eacute;quipementier partenaire des constructeurs automobiles et des acteurs de la nouvelle mobilit&eacute; dans le monde entier. Notre vision ? Inventer une mobilit&eacute; plus verte et plus s&ucirc;re, gr&acirc;ce &agrave; des solutions ax&eacute;es sur la conduite intuitive et la r&eacute;duction des &eacute;missions de CO2. Nous sommes leaders dans nos domaines d'activit&eacute; et reconnus comme l'une des plus grandes entreprises innovantes au monde.
 
 
 Responsibilities Cross-Disciplinary Automation
 
 ~
 
 Design and implement AI workflows that bridge the gap between Systems Engineering and downstream disciplines (HW, SW, Mech) to ensure seamless requirements traceability and consistency.
 
 
 Physics-Informed Modeling~ Develop and deploy Physics-Informed Machine Learning (PIML) models to accelerate simulations in Mechanics and Electrotechnique.
 
 
 
 AI-Enhanced System Engineering
 
 ~ Integrate AI-assisted coding, automated unit testing, and bug prediction tools into the software development pipeline in compliance with ASPICE standards.
 
 
 
 Predictive Project Management
 
 ~ Build predictive analytics dashboards for Technical Project Managers to forecast resource bottlenecks, budget risks, and milestone delays using historical project data.
 
 
 
 Standards &amp; Compliance~
 
 Ensure all AI-automated processes and generated outputs adhere to ISO 26262 (Functional Safety) and ISO/SAE 21434 (Cybersecurity) requirements.
 
 
 
 Toolchain Integration
 
 ~ Lead the integration of AI agents with existing toolchains, including PLM, ALM (Codebeamer), and MATLAB/Simulink.
 
 
 Key competencies
 
 Technical Skills
 
 
 
 AI and Machine Learning
 
 
 <ul>
 <li>
 Generative AI &amp; LLMs
 </li>
 <li>
 Predictive Modeling
 </li>
 <li>
 Computer Vision
 
 
 </li>
 </ul>
 Data Engineering and Management
 
 
 <ul>
 <li>
 Data Pipeline Construction~ Automating the flow of data into AI models.
 </li>
 <li>
 Data Quality Assurance~ Cleaning and labeling datasets to ensure the AI isn't learning from "noise."
 
 
 </li>
 </ul>
 
 Process Automation &amp; Integration (MLOps)
 
 
 
 <ul>
 <li>
 Workflow Orchestration~ Using tools to connect AI outputs to other R&amp;D software (like ELNs or LIMS).
 </li>
 <li>
 Deployment~ Ensuring the AI tools are accessible via user-friendly interfaces.
 
 
 </li>
 </ul>
 Programming &amp; Scripting~
 
 
 <ul>
 <li>
 Python
 </li>
 <li>
 Javascript / Google Apps Script
 </li>
 <li>
 Google Docs / Sheets functions &amp; automation
 </li>
 <li>
 HTTP rest API's
 
 
 </li>
 </ul>
 Tooling &amp; ALM~ ( Plus Knowledge)
 
 
 <ul>
 <li>
 Codebeamer (Requirement Management Tool)
 </li>
 <li>
 Google Cloud Platform
 
 
 </li>
 </ul>
 Automation &amp; Integration concepts
 
 
 <ul>
 <li>
 AI &amp; Data Handling~
 </li>
 <li>
 Basic to intermediate experience with AI tools, APIs, or AI agents
 </li>
 <li>
 Interest in applying AI to engineering processes
 
 
 </li>
 </ul>
 Soft Skills
 
 
 <ul>
 <li>
 Strong communication and collaboration skills, including ability to translate technical AI capabilities into tangible benefits for the teams
 </li>
 <li>
 Ability to work autonomously and proactively
 </li>
 <li>
 Analytical mindset with strong problem-solving skills
 </li>
 <li>
 User-oriented mindset (training, support, feedback handling)
 </li>
 <li>
 Time Managment
 
 
 </li>
 </ul>
 Nice to Have
 
 
 Experience with requirement traceability or compliance activities
 
 
 Exposure to AI-assisted automation or low-code/no-code platforms
 
 
 Physics-Informed Machine Learning (PIML)
 
 
 Predictive Project Analytics
 
 
 Understanding of system engineering lifecycle and deliverables
 
 
 
 Aware About Automotive Industry And Embedded Systems.
 
 
 
 Years of Experience 2 to 3 years experience in AI &amp; tools development
 
 
 
 Position~
 
 
 
 AI4all, Engineering Disciplines
 
 
 
 D&eacute;partement~
 
 
 
 GTSC Software
 
 
 
 Schedule~
 
 
 
 Temps plein
 
 
 
 Employee Status~
 
 
 
 CDI
 
 
 
 Type de contrat~
 
 
 
 
 Job Posting Date~
 
 
 
 2026-04-07
 
 
 
 Join Us !
 
 
 Being part of our team, you will join~
 
 
 <ul>
 <li>
 one of the largest global innovative companies, with more than 20,000 engineers working in Research &amp; Development
 </li>
 <li>
 a multi-cultural environment that values diversity and international collaboration
 </li>
 <li>
 more than 100,000 colleagues in 31 countries... which make a lot of opportunity for career growth
 </li>
 <li>
 a business highly committed to limiting the environmental impact if its activities and ranked by Corporate Knights as the number one company in the automotive sector in terms of sustainable development
 
 
 </li>
 </ul>
 More information on Valeo~ https~//www.valeo.com
 
</div>

sonnen Egypt

<div>
 
 Standort
 
 
 
 Cairo, EG
 
 
 
 Stellen-ID
 
 : 4758
 
 
 Join the energy revolution with #teamsonnen!
 
 
 At sonnen, we&rsquo;re driven by a clear goal: creating a future powered by clean, affordable energy for everyone. That&rsquo;s why we make our customers independent &ndash; not only from fossil fuels, but also from rising electricity costs.
 
 
 The key to this independence is our intelligent, all-in-one energy system. It combines solar panels, battery storage, energy tariffs, and wallboxes &ndash; all developed and manufactured in Germany.
 
 
 As the first and only provider in Germany, we also connect thousands of home batteries into one shared network: the sonnenVPP, our industry-leading virtual power plant.
 
 
 In short: every day, we&rsquo;re working to shape the energy future. And we&rsquo;d be thrilled to have you join us!
 
 
 We are seeking a Data Engineer (m/f/d) to join our team and play a pivotal role in enabling our Business Intelligence and Data Science teams. As a Data Engineer, you will be responsible for maintaining and enhancing our AWS-based analytics platform, provisioning data from various sources, and enabling the development and stable operation of analytical solutions. We&rsquo;re looking for someone who shares our values, who isn&rsquo;t afraid to challenge existing processes, and who would like to work on innovative solutions in a fast-moving environment. If this sounds like you, then don&rsquo;t hesitate to get in touch.
 
 
 
 What you will do to help drive the energy transition:
 
 
 
 <ul>
 <li>
 (Senior) Define and design the architecture of our analytics platform, ensuring scalability, performance, and reliability.
 </li>
 <li>
 You design and build scalable data pipelines, ETL processes, and data lake and data warehousing solutions to support our analytics solutions.
 </li>
 <li>
 You develop and maintain data integration processes with a variety of structured and unstructured data sources.
 </li>
 <li>
 You implement, test, and maintain infrastructural components of sonnen&rsquo;s analytics platform and deploy and maintain data models.
 </li>
 <li>
 You implement data quality checks and monitoring mechanisms to ensure accuracy, completeness, and consistency of data.
 </li>
 <li>
 You define coding principles and support data scientists and analysts in implementing algorithms into operational solutions.
 </li>
 <li>
 Adhere to stringent quality assurance and documentation standards, utilizing version control and code repositories such as Gitlab.
 </li>
 <li>
 You stay up to date with emerging trends and technologies in data engineering and assess their potential applications to our business needs.
 </li>
 <li>
 (Senior) Share your knowledge by coaching/pair coding with more junior engineers.
 
 
 </li>
 </ul>
 
 What You Will Need On That Journey
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer science or a related technical field.
 </li>
 <li>
 +3 years of relevant employment experience in roles such as Data Scientist, Data Engineer, or Data Architect.
 </li>
 <li>
 +3 years of experience with ETL tools, Data Modeling, and Data Architecture.
 </li>
 <li>
 Experience with Big Data technologies such as Hadoop, Hive, and Spark.
 </li>
 <li>
 Ability to translate organizational goals into technical solutions.
 </li>
 <li>
 Experience with Infrastructure as Code (experience in Terraform and Ansible are a plus).
 </li>
 <li>
 Proficiency in Python, SQL, and NoSQL.
 </li>
 <li>
 Excellent communication and project management skills.
 
 
 </li>
 </ul>
 
 Stellensegment:
 
 Quality Assurance, Computer Science, Data Warehouse, Business Intelligence, Database, Technology
</div>

Data Engineer (m/f/d)

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>

Explore 328+ Analytics engineer in Cairo this April. Find roles across top companies and apply now to boost your career.

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