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senior data engineer

Celfocus

<div>
 
 Make an impact
 
 by working for sectors where technology is the enabler, everything is ground-breaking and there&rsquo;s a constant need to be innovative.
 
 
 
 Create and enhance projects
 
 in Java, Python, Angular, PHP, .NET and so much more while diving in the world of Blockchain, Artificial Intelligence, Data Science, Security and Internet of Things.
 
 
 
 Be part of the team
 
 that combines business knowledge, technological edge and a design experience. Our different backgrounds and know-how are key in developing solutions and experiences for digital clients.
 
 
 
 Face challenges
 
 and learn other ways of thinking and seeing the world - there&rsquo;s always room for your energy and creativity.
 
 
 
 About The Role
 
 
 
 Data Engineer is responsible for building and maintaining Data Platforms. Recognizes the importance of data for the organization in the areas where it is the key to success. Maintaining an eye on the big picture and knowing the details of the business are decisive for this role.
 
 
 This role is focused on designing, developing, and maintaining the data platform required for data storage, processing, orchestration, and analysis.
 
 
 The mission involves implementing scalable and performant data pipelines and data integration solutions.
 
 
 Agnostic of data sources and technologies to ensure efficient data flow and high data quality, enabling data scientists, analysts, and other stakeholders to access and analyze data effectively.
 
 
 
 As a part of your job, you will:
 
 
 
 <ul>
 <li>
 Design, build, and maintain scalable data platforms
 </li>
 <li>
 Collect, process, and analyze large and complex data sets from various sources
 </li>
 <li>
 Develop and implement data processing workflows using data processing framework technologies
 </li>
 <li>
 Collaborate with cross-functional teams to ensure data accuracy and integrity
 </li>
 <li>
 Ensure data security and privacy through proper implementation of access controls and data encryption
 </li>
 <li>
 Extraction of data from various sources, including databases, file systems, and APIs
 </li>
 <li>
 Monitor system performance and optimize for high availability and scalability
 
 
 
 </li>
 </ul>
 
 What are we looking for?
 
 
 
 <ul>
 <li>
 8-9 years of experience with cloud platforms and services for data engineering (GCP and/or AWS and/or Azure)
 </li>
 <li>
 Proficiency in programming languages like Python, Java, or Scala
 </li>
 <li>
 Use of Big Data Tools such as Spark, Flink, Kafka, Elastic Search, Hadoop, Hive, Sqoop, Flume, Impala, Kafka Streams and Connect, Druid, etc.
 </li>
 <li>
 Knowledge of data modeling and database design principles
 </li>
 <li>
 Familiarity with data integration and ETL tools (e.g., Apache Kafka, Talend)
 </li>
 <li>
 Understanding of distributed systems and data processing architectures
 </li>
 <li>
 Strong SQL skills and experience with relational and NoSQL databases
 </li>
 <li>
 Familiarity with cloud platforms and services for data engineering (e.g., AWS S3, Azure Data Factory)
 </li>
 <li>
 Experience with version control tools such as Git
 
 
 
 </li>
 </ul>
 
 Nice to have:
 
 
 
 <ul>
 <li>
 Problem solving and analytical mindset
 </li>
 <li>
 Strong communication skills
 </li>
 <li>
 Proven ability to work independently and remotely
 </li>
 <li>
 Experience with Agile and Lean methodologies
 </li>
 <li>
 Leadership of small technical teams
 
 
 
 </li>
 </ul>
 
 Personal traits
 
 
 
 <ul>
 <li>
 Ability to adapt to different contexts, teams, and Clients;
 </li>
 <li>
 Teamwork skills but also a sense of autonomy;
 </li>
 <li>
 Motivation for international projects and ok if travel is included;
 </li>
 <li>
 Willingness to collaborate with other players;
 </li>
 <li>
 Strong communication skills.
 
 
 
 </li>
 </ul>
 At Celfocus, we are committed to cultivate a diverse and inclusive workplace. As an equal-opportunity employer, we welcome applicants of all backgrounds, gender identities, and abilities. We are dedicated to providing reasonable accommodations for candidates with specific needs. If you require any adjustments during the selection process, please inform our Talent Acquisition Team.
 
 
 
 Come join the Team!
 
 
 
 
 Celfocus is pioneering the future of business through Next-Gen Intelligence - the convergence of data, AI, and human creativity to build more autonomous and adaptive organisations.
 
 
 
 Guided by our core belief - Making Data Actionable - we partner with leading companies to co-create intelligent solutions that turn data into insight, agility, and business value.
 
 
 Operating in over 25 countries, we bring together business experts, data scientists, and AI engineers to turn complexity into clarity and vision into measurable impact.
 
 
 Founded in 2000, Celfocus is part of Novabase, listed on Euronext Lisbon.
 
 
 To know more, visit www.celfocus.com
</div>

Senior Data Engineer

HireOn

<div>
 
 Senior Data Engineer
 
 
 
 
 Location:
 
 Cairo, Egypt (Onsite)
 
 
 
 Experience:
 
 8&ndash;12 Years
 
 
 
 Employment Type:
 
 Full-Time
 
 
 
 Salary Range:
 
 80,000 EGP &ndash; 160,000 EGP per month
 
 
 
 The Opportunity
 
 
 
 HireOn is recruiting for its reputed international client seeking a
 
 Senior Data Engineer
 
 to lead the architecture and delivery of enterprise-grade data platforms.
 
 
 This role goes beyond pipeline development &mdash; it requires ownership of scalable architecture, performance optimization, governance, and cross-functional collaboration. The ideal candidate is a hands-on senior engineer capable of designing robust cloud-native data ecosystems while mentoring engineers and driving technical standards.
 
 
 
 What You Will Own
 
 
 
 <ul>
 <li>
 End-to-end design of batch and real-time data pipelines
 </li>
 <li>
 Enterprise data warehouse architecture and modeling strategy
 </li>
 <li>
 Workflow orchestration and automation frameworks
 </li>
 <li>
 Performance tuning and cost optimization initiatives
 </li>
 <li>
 Data governance, cataloging, and access control frameworks
 </li>
 <li>
 Monitoring, logging, and observability implementation
 </li>
 <li>
 Technical mentorship and architecture reviews
 
 
 </li>
 </ul>
 
 Technical Environment
 
 
 
 You will work extensively with modern cloud-native data technologies including:
 
 
 AWS Glue, Amazon EMR (Spark), AWS Lambda, Apache Airflow (MWAA), Amazon Redshift, Amazon S3, Amazon DynamoDB, Amazon EC2, Amazon CloudWatch, AWS DataZone
 
 
 
 Core Expertise Required In
 
 
 
 Python, Advanced SQL, Data Warehousing (Star/Snowflake), ETL/ELT best practices, Distributed Data Processing Systems
 
 
 
 What Makes You a Strong Fit
 
 
 
 <ul>
 <li>
 8&ndash;12 years of experience in Data Engineering
 </li>
 <li>
 Strong experience designing scalable cloud-based data architectures
 </li>
 <li>
 Proven ability to independently drive technical solutions
 </li>
 <li>
 Experience mentoring engineers and contributing to architectural decisions
 </li>
 <li>
 Strong communication skills for cross-functional collaboration
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Cloud Professional Certifications
 </li>
 <li>
 Experience with streaming platforms (Kinesis/Kafka)
 </li>
 <li>
 Exposure to metadata management and data lineage
 </li>
 <li>
 Experience working with enterprise-scale data platforms
 
 
 </li>
 </ul>
 Skills: aws glue,etl,amazon redshift,aws lambda,aws emr,snowflake
</div>

Senior Data Engineer (Onsite | Cairo, Egypt)

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>

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:
 
 Computer Science, Data Warehouse, Quality Assurance, Business Intelligence, Project Manager, Technology
</div>

Data Engineer (m/f/d)

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

Arrow Electronics

<div>
 
 Position
 
 
 
 Data Scientist / Senior Machine Learning Engineer
 
 
 
 Job Description
 
 
 
 
 Position Overview:
 
 
 
 As Data Scientist / Senior Machine Learning Engineer at Arrow Electronics, you will assume a pivotal role in driving our data science and machine learning initiatives to reach unprecedented heights. Collaborating closely with cross-functional multinational teams, your responsibilities will encompass the end-to-end machine learning lifecycle, including stakeholder communications, data analysis, designing, development, deployment, and optimization of cutting-edge models aimed at addressing intricate challenges and generating actionable insights. Your expertise in data analysis, model development, and deployment will be crucial in shaping the future of our company.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Machine Learning Model Development: Design, develop, and implement advanced machine learning models and algorithms to solve real-world problems in various domains.
 </li>
 <li>
 Data Analysis: Explore and analyze large datasets to extract meaningful insights and identify trends, anomalies, and patterns.
 </li>
 <li>
 Model Evaluation: Evaluate the performance of machine learning models using appropriate metrics and fine-tune models for optimal results.
 </li>
 <li>
 Deployment: Lead the deployment of machine learning models into production environments and ensure scalability and efficiency.
 </li>
 <li>
 Cross-functional Collaboration: Collaborate closely with business stakeholders, software engineers, data engineers, and domain experts to integrate machine learning solutions into our products and services.
 </li>
 <li>
 Mentorship: Provide guidance and mentorship to junior data scientists and machine learning engineers, fostering a culture of continuous learning and growth.
 </li>
 <li>
 Research and Innovation: Stay up-to-date with the latest advancements in the field of data science and machine learning and apply innovative techniques to solve complex challenges.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Proven experience (2 to 5 years) in developing and deploying machine learning models in a production environment.
 </li>
 <li>
 Proficiency in programming languages, especially Python, and experience with data-related libraries such as pandas, matplotlib, NumPy, etc.
 </li>
 <li>
 Strong knowledge of machine learning frameworks and libraries.
 </li>
 <li>
 Expertise in data preprocessing, feature engineering, and model selection.
 </li>
 <li>
 Familiarity with large language models and AI agent design.
 </li>
 <li>
 Experience with text-based NLP, information extraction, entity recognition, and text-related data science tasks is highly desirable.
 </li>
 <li>
 Strong communication skills and the ability to convey technical concepts to non-technical stakeholders.
 </li>
 <li>
 Experience with vectorized databases and unstructured search engines is a plus.
 </li>
 <li>
 A Master&rsquo;s degree in computer science, Statistics, Data Science, or a related field is a plus.
 </li>
 <li>
 Publications or contributions to open-source projects are a plus.
 
 
 </li>
 </ul>
 If you are a passionate and experienced Data Scientist / Senior Machine Learning Engineer who thrives on solving challenging problems and wants to make a significant impact in the field, we encourage you to apply and join our dynamic team at Arrow Electronics Together, we will drive innovation and shape the future of data science and machine learning.
 
 
 
 Location:
 
 
 
 EG-Cairo, Egypt (Al Emdad &amp; Al Tamween)
 
 
 
 Time Type
 
 
 
 Full time
 
 
 
 Job Category
 
 
 
 Information Technology
</div>

Data Scientist / Senior Machine Learning Engineer

Siemens

<div>
 
 About Brightly
 
 
 
 Brightly is a global leader in intelligent, cloud‑based asset lifecycle management, empowering 12,000+ clients with predictive insights to optimize maintenance, energy, and capital planning&mdash;backed by Siemens. Our products help schools, hospitals, cities, and manufacturers keep critical infrastructure running efficiently and sustainably.
 
 
 
 The Opportunity
 
 
 
 We&rsquo;re looking for a Senior Machine Learning Engineer to lead LLM‑powered application development&mdash;from prototype to production&mdash;on AWS. You&rsquo;ll design robust ML/LLM services that power search, recommendations, copilots, and workflow automation in Brightly&rsquo;s platform, partnering closely with product, data, and engineering teams. Responsibilities and skill expectations reflect current industry practice for senior ML/LLM engineers, including end‑to‑end model lifecycle ownership, production‑grade code, and MLOps.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Build LLM applications: Design and implement RAG pipelines, prompt orchestration, tools/agents, safety/guardrails, and evaluation harnesses; instrument for latency, cost, and quality. (Guided by current LLM engineer role practices.)
 </li>
 <li>
 Own the ML lifecycle: Data curation, feature engineering, training/fine‑tuning (LoRA/QLoRA), A/B testing, deployment, monitoring, and continuous improvement of models and prompts.
 </li>
 <li>
 Productionize on AWS: Ship scalable services on EKS/ECS/Lambda; leverage SageMaker, Bedrock, EMR, MSK, Step Functions; apply observability (CloudWatch/OpenTelemetry) and cost controls. (Duties aligned to modern AWS ML roles.)
 </li>
 <li>
 Scale training &amp; inference: Use distributed training (FSDP/DeepSpeed), quantization, caching, vector databases, and GPU/Inferentia for performance and efficiency.
 </li>
 <li>
 MLOps &amp; governance: Establish CI/CD for models (MLflow/Kedro/SageMaker Pipelines), model/version registries, data and prompt lineage, evaluation gates, and responsible‑AI controls. (Aligned with contemporary MLOps templates.)
 </li>
 <li>
 Partner across Brightly: Translate asset‑management use cases into ML/LLM solutions; collaborate with product managers and UX to ship customer‑visible features that measurably improve reliability, safety, and sustainability.
 </li>
 <li>
 Mentor &amp; lead: Provide technical leadership, review designs/PRs, and raise the bar on ML engineering excellence across the team. (Common senior ML expectations.)
 </li>
 <li>
 Perform Exploratory Data Analysis (EDA) on structured, semi‑structured, and unstructured datasets to identify patterns, correlations, feature importance, and data quality issues.
 
 
 </li>
 </ul>
 (Consistent with ML engineer responsibilities to analyze data before model development.)
 
 
 <ul>
 <li>
 Conduct deep research on asset-related, operational, and domain-specific datasets to understand root causes, trends, and predictive signals.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Bring
 
 
 
 
 Required experience
 
 
 
 <ul>
 <li>
 8&ndash;10 years total software/ML engineering experience, with 5+ years building and operating ML systems in production.
 </li>
 <li>
 1+ years hands‑on LLM application development (e.g., RAG, fine‑tuning, prompt engineering, evaluators/guardrails, agentic workflows) using packages such as Langchain and Langgraph.
 </li>
 <li>
 AWS proficiency (3+ years): Strong with core services (EKS/ECS, Lambda, S3, DynamoDB/RDS, Step Functions, IAM) and ML stack (SageMaker, Bedrock or HF on AWS). (Representative AWS ML role skills.)
 </li>
 <li>
 Modeling &amp; frameworks: Python, PyTorch, Hugging Face ecosystem; vector stores (e.g., OpenSearch, PGVector, Pinecone), embeddings, retrieval, and evaluation metrics for NLP/LLMs. (In line with senior LLM roles.)
 </li>
 <li>
 MLOps: CI/CD for ML, model registries, experiment tracking, telemetry/monitoring, automated retraining; Docker/Kubernetes, GitHub Actions/GitLab CI. (Current MLOps expectations.)
 </li>
 <li>
 Data engineering fluency: ETL/ELT, streaming/batch (Spark/Flink), data quality and governance controls for ML.
 
 
 </li>
 </ul>
 
 Nice to have
 
 
 
 <ul>
 <li>
 Experience with distributed training (FSDP, DeepSpeed), RLHF, or Inferentia/Trainium optimization.
 </li>
 <li>
 Exposure to sustainability/asset/intelligent operations domains.
 </li>
 <li>
 Familiarity with security &amp; compliance for ML systems in enterprise environments. (Frequently included in senior ML roles.)
 
 
 </li>
 </ul>
 
 How You&rsquo;ll Work
 
 
 
 <ul>
 <li>
 Pragmatic and product‑oriented: You bias to measurable outcomes and iterate quickly with stakeholders. (Modern senior ML role framing.)
 </li>
 <li>
 Engineering excellence: You write production‑quality Python, design reliable APIs/services, and uphold testing/observability standards. (Common duties in senior templates.)
 </li>
 <li>
 Collaborative leadership: You mentor peers and influence architecture across teams. (Industry‑standard senior expectations.)
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s in CS/EE/Math or related field (Master&rsquo;s preferred) or equivalent practical experience. (Typical for senior ML roles.)
 
 
 </li>
 </ul>
 Join a mission‑driven team building technology that keeps communities running&mdash;safer, greener, and more resilient&mdash;at global scale. You&rsquo;ll pair startup‑speed product work with the reach and rigor of Siemens.
 
 
 
 The Brightly culture
 
 
 
 We&rsquo;re guided by a vision of community that serves the ambitions and wellbeing of all people, and our professional communities are no exception. We model that ideal every day by being supportive, collaborative partners to one another, conscientiously making space for our colleagues to grow and thrive. Our passionate team is driven to create a future where smarter infrastructure protects the environments that shape and connect us all. That brighter future starts with us.
</div>

Principal Machine Learning Engineer

Explore 517+ Senior data engineer in Cairo this March. Find roles across top companies and apply now to boost your career.

517 senior data engineer jobs In Cairo

Senior Data Engineer

Senior Data Engineer (Onsite | Cairo, Egypt)

Senior Data Engineer

Data Engineer (m/f/d)

Senior Data & Applied AI Engineer

Data Scientist / Senior Machine Learning Engineer

Principal Machine Learning Engineer