وظائف التكنولوجيا وتقنية المعلومات

We are looking for Senior Data Analyst who has deep technical analytics with business partnership. In this role you aren't just expected to build dashboards, you're expected to own the entire analytical lifecycle and influence business decisions. What you'll do: Own analytics for one or more business domains (such as Lending, Payments, Risk, Sales, or Growth), acting as the primary analytics partner for stakeholders Translate ambiguous business questions into clear analytical problems, delivering actionable insights that drive decision-making Build, maintain, and govern trusted metrics and dashboards in Looker using LookML, ensuring consistent definitions and a reliable single source of truth Conduct advanced analyses, including funnel diagnostics, cohort analysis, segmentation, churn and activation analysis, and causal inference, to uncover not just what happened, but why Partner directly with senior stakeholders to scope requests, prioritize work, communicate findings, and confidently present analytical recommendations Ensure data quality by validating datasets, reconciling discrepancies, and identifying limitations related to data availability or privacy requirements Contribute to the analytics platform by improving documentation, semantic models, coding standards, and best practices that enable the team to scale Communicate insights through concise dashboards, presentations, and documentation tailored to different audiences To succeed in this role, you'll need to have: 5+ years of experience in data analytics, including at least 2 years operating independently in a senior individual contributor capacity Background in fintech or banking is strongly preferred Advanced SQL with strong understanding of complex datasets and multi-row relationships Experience with cloud data warehouses such as BigQuery (preferred), Snowflake, or Redshift Strong experience building governed BI solutions in Looker/LookML or comparable platforms such as Tableau or Power BI Experience with dbt or similar data transformation frameworks Working knowledge of Python or R for analysis and automation Strong foundation in statistics, experimentation, and causal analysis (A/B testing, cohort analysis, regression, diff-in-diff, regression discontinuity, etc.) Ability to transform ambiguous business questions into well-scoped analytical projects Strong analytical judgment and methodological rigor Excellent stakeholder management and communication skills Commitment to data quality, governance, and consistent metric definitions Ability to work autonomously and own projects from problem definition through delivery Show more

Main Responsibilities Sales Performance Analysis Analyze sales by product, sales representative, territory/region, and customer segment. Identify trends, opportunities, and performance gaps. Track achievement against sales targets and budgets. Dashboard & Reporting Create and maintain dashboards for management. Prepare daily sales reports, weekly performance reviews, monthly business reviews, and forecast reports. Ensure data accuracy and consistency. Forecasting & Planning Support sales forecasting. Analyze historical sales trends. Predict future demand and revenue. Help management set realistic targets. Customer Analysis Analyze customer purchasing behavior. Identify high-value customers, customers at risk of leaving, and growth opportunities within accounts. Support customer segmentation strategies. Pricing & Profitability Analysis Analyze gross margins, product profitability, discount impact, and customer profitability. Recommend actions to improve profitability. CRM & Data Quality Management Monitor CRM data quality. Ensure opportunities, customer records, and sales activities are correctly recorded. Identify missing or inaccurate data. Business Intelligence Support Build reports using Microsoft Power BI, Tableau, Microsoft Excel, and SQL Server. Automate reporting processes where possible. Key KPIs for a Sales Data Analyst Report Accuracy % Dashboard Adoption Rate Forecast Accuracy % Data Quality Score Time Required to Generate Reports Number of Actionable Insights Implemented Revenue Opportunities Identified Margin Improvement Recommendations Requirements Qualifications – Sales Data Analyst Bachelor’s degree in Business Administration, Economics, Finance, Statistics, Data Analytics, Computer Science, or a related field. 5-7 years of experience in Sales Analysis, Business Intelligence, Data Analysis, Commercial Analytics, or a related role. Strong experience in sales performance analysis, forecasting, reporting, and business analytics. Advanced proficiency in Microsoft Excel, including Pivot Tables, Power Query, formulas, and data analysis. Hands-on experience with Microsoft Power BI and dashboard development. Good knowledge of SQL Server and the ability to extract, manipulate, and analyze data from databases. Knowledge of Tableau is an advantage. Strong understanding of sales KPIs, revenue, margins, targets, forecasting, and profitability analysis. Experience working with CRM systems and maintaining data accuracy and quality. Strong analytical and problem-solving skills with the ability to translate data into actionable business insights. Excellent attention to detail and ability to identify data discrepancies and performance gaps. Strong communication and presentation skills, with the ability to present complex data in a clear and management-friendly manner. Ability to work with large datasets and manage multiple reporting requirements within deadlines. Experience in the medical devices, pharmaceutical, FMCG, or distribution sectors is a plus. Show more

Responsibilities Manage and monitor AWS cloud infrastructure and services and ensure the reliability and availability of production environments. Deploy, manage, and scale containerized applications using Kubernetes and Helm. Design, maintain, and improve CI/CD pipelines using Jenkins and Git-based workflows, including Bitbucket. Implement and maintain infrastructure using Infrastructure as Code (IaC) tools such as Terraform; experience with Terragrunt is a plus. Support GitOps-based deployments, with experience in Argo CD considered a strong advantage. Manage Docker containers and containerized application environments. Monitor system performance, availability, and application health, and troubleshoot production issues. Maintain and improve logging, monitoring, alerting, and system automation. Support and manage production databases and caching systems, including MySQL/MariaDB and Redis. Work with Linux systems and develop automation scripts using Bash and/or Python. Collaborate closely with development and engineering teams to streamline deployments and improve system reliability. Troubleshoot infrastructure, networking, deployment, and production-related issues. Contribute to infrastructure optimization, security, scalability, and cloud cost management. Communicate clearly with engineers, external partners, and non-technical stakeholders when required. Qualifications 2–3 years of hands-on experience in DevOps, SRE, Platform Engineering, or a similar role, preferably with production responsibility. Strong hands-on experience with: AWS Cloud Services such as EC2, S3, IAM, and related services. Kubernetes cluster management, deployments, and scaling. Helm for Kubernetes package management. Docker and containerization. Linux systems administration and troubleshooting. Git workflows and CI/CD practices. Jenkins or similar CI/CD automation tools. Terraform for infrastructure provisioning and management. Good understanding of networking fundamentals, including DNS, load balancers, TLS, and firewalls. Experience working with MySQL/MariaDB and Redis in production environments. Experience with Bash and/or Python scripting. Good troubleshooting and problem-solving skills. Strong communication skills and the ability to collaborate effectively with technical and non-technical stakeholders. Ability to work independently, prioritize tasks, and operate effectively in a fast-paced environment. Nice to Have Experience with GitOps and Argo CD. Experience with Terragrunt. Knowledge of Huawei Cloud services. AWS certifications, such as Cloud Practitioner or Solutions Architect Associate. Experience with monitoring and observability tools such as Prometheus, Grafana, and ELK Stack. Experience with cloud cost optimization and management. Experience with Ansible or other automation/configuration management tools. Show more

We are seeking a skilled and experienced Principal DevOps/SysOps Engineer to join our innovative team. The ideal candidate possesses a strong knowledge in Linux Servers administration, Managing clusters, monitoring tools, containerization (Docker and Kubernetes), cloud platforms (AWS, Azure, Google), infrastructure-as-code (Terraform and Ansible), and scripting languages using Bash and Python. If you are a seasoned professional with a deep understanding of the software development lifecycle, we invite you to apply and contribute to our dynamic and collaborative environment. If you are a passionate and experienced Principal DevOps/SysOps Engineer with a comprehensive skill set, including expertise in Linux, we encourage you to apply and contribute to our cutting-edge projects and initiatives. Responsibilities: Deploy, configure, and maintain Linux and Windows servers across physical and virtual environments Strong knowledge of HPC cluster management, job scheduling systems like SLURM or Run:AI Hands on experience of Docker containers and Kubernetes, implementation, administration and optimization within complex large scale environments Proven experience as a DevOps Engineer with a focus on CI/CD, containerization, GitOps and cloud technologies Proficiency in scripting languages such as Bash, Python for automation and performance tuning Experience with high-speed interconnects (Infiniband, Ethernet), distributed storage systems, and cluster networking Configure and maintain firewalls, load balancers, and VPNs Proven ability to troubleshoot complex system and networking issues in large-scale clusters Install and utilize monitoring tools to ensure the health, performance, and security of systems Worked with at least one major cloud provider (AWS, Azure, or Google) to deploy and manage cloud-based solutions Apply knowledge of cybersecurity best practices to enhance the security posture of systems Utilize infrastructure-as-code tools like Terraform and Ansible for efficient and reproducible infrastructure deployment Possess a good understanding of the software development lifecycle to collaborate effectively with development teams Requirements Bachelor's degree in Computer Science, Information Technology, or a related field with 8+ years of experience Proven experience as a DevOps Engineer with a focus on CI/CD, containerization, and cloud technologies Strong knowledge and hands-on experience with Docker containers and Kubernetes Interaction with at least one major cloud provider (AWS, Azure, or Google) Understanding and application of cybersecurity principles Proficiency in infrastructure-as-code tools like Terraform and Ansible Excellent scripting skills in Bash and Python Familiarity with the software development lifecycle Strong knowledge of Linux operating systems Preferred Experience: CKA/CKAD/CKS certification Certifications in relevant DevOps, cloud, and cybersecurity domains Additional scripting languages and automation tool proficiency Active participation in community forums or open-source projects Benefits Salary paid in USD Six-month career advancing opportunities Employee parking space Supportive and friendly work environment Premium medical insurance [employee +family] English language development courses Interest-free loans paid over 2.5 years Technical development courses Planned overtime program (POP) Employment referral program Premium location in Maadi Social insurance Show more

About Mozn MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence. We're a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact. If you're passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises. About the role We are looking for a highly motivated AI Infrastructure Engineer III to join our Cloud Engineering team. The ideal candidate is passionate about building scalable AI infrastructure that enables machine learning engineers and data scientists to efficiently develop, train, deploy, and operate AI models. This role focuses on designing, operating, automating, and continuously improving AI platform capabilities including Kubeflow, MLflow, GPU infrastructure, distributed training platforms, model serving infrastructure, and MLOps tooling across cloud-native and hybrid environments. The ideal candidate possesses deep expertise in AI infrastructure and GPU platforms. Kubernetes and cloud platform experience are essential enablers, but the primary focus is building highly optimized infrastructure for AI and machine learning workloads. What you'll do AI Platform Engineering Design, deploy, and operate enterprise AI/ML platforms. Build self-service platforms for Data Scientists and ML Engineers. Deploy and operate Kubeflow, MLflow, KServe, Ray, or similar AI platforms. Design infrastructure supporting model training, experimentation, feature engineering, and inference. Build highly available and scalable model serving infrastructure. GPU Infrastructure Design and operate GPU clusters for large-scale AI workloads. Optimize GPU scheduling, utilization, sharing, autoscaling, and resource allocation. Deploy and manage NVIDIA GPU Operator and GPU-enabled Kubernetes environments. Optimize distributed GPU training performance across multi-node clusters. Troubleshoot AI infrastructure performance bottlenecks. MLOps & Platform Automation Build CI/CD pipelines for ML workloads. Automate AI infrastructure provisioning using Infrastructure as Code. Implement monitoring and observability for GPU utilization, model serving, training jobs, and inference latency. Collaborate closely with Data Science teams to improve platform usability, performance, and reliability. Requirements 4-6 years of experience in AI Infrastructure, MLOps, Platform Engineering, or Cloud Engineering. Strong hands-on experience with Kubernetes. Experience with Kubeflow, MLflow, or similar ML platform technologies. Experience operating GPU infrastructure for AI workloads. Strong understanding of NVIDIA GPU technologies, CUDA fundamentals, and GPU optimization. Experience supporting distributed training workloads. Experience with model serving platforms such as KServe, Triton Inference Server, Ray Serve, or similar. Experience with AWS, GCP, OCI, or Azure AI platforms. Experience automating infrastructure using Terraform, Helm, GitOps, or Ansible Strong scripting or programming skills in Python, Bash, or Go. Experience with Prometheus, Grafana, OpenTelemetry, ELK/OpenSearch, or equivalent observability platforms. Preferred Qualifications Experience with PyTorch, TensorFlow, Hugging Face, or JAX. Experience with distributed training frameworks such as Ray, DeepSpeed, Horovod, or NCCL. Experience with Vector Databases, LLM infrastructure, RAG architectures, or GenAI platforms. Experience operating inference platforms for large language models. Experience supporting AI research or Data Science teams in production environments. Contributions to Cloud Native, Kubernetes, AI, or ML open-source communities Cloud, Kubernetes, NVIDIA, or AI/ML certifications are a plus. Benefits You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves Show more

About Blnk blnk is a fintech company with a mission of enabling inclusion through point-of-sale financing. Less than 4% of Egyptians have access to credit cards and can only afford to purchase products/services with cash that they have saved or are forced to borrow from hard money lenders at high interest rates. We’re changing this by enabling all consumers to instantly receive credit within minutes at their favorite merchants. Job Scope The primary objective of the Backend Developer is to design, develop, and maintain robust and scalable backend systems that power applications and services. This role involves collaborating closely with cross-functional teams to understand business requirements, architecting efficient solutions, and ensuring the seamless integration of backend services with frontend and other systems. The Backend Developer is expected to adhere to best practices, ensure high performance and security, and contribute to the continuous improvement of the development lifecycle. Key Responsibilities Design and implement high-quality, scalable, and maintainable backend solutions using different programming languages like python or C++. Develop and maintain RESTful APIs to support application functionality and third-party integrations. Ensure system responsiveness, reliability, and scalability. Design, implement, and optimize database schemas and queries. Work with relational databases like PostgreSQL or MySQL,ensuring data integrity and performance. Implement data migrations and versioning effectively. Collaborate with architects and other developers to design system architecture aligned with business goals. Implement microservices or modular architectures where applicable to improve scalability and maintainability. Write unit tests, integration tests, and conduct performance testing to ensure high code quality. Debug and resolve issues in the production environment efficiently. Work closely with front-end developers, product managers,and other stakeholders to deliver end-to-end features. Participate in code reviews to maintain high standards and share knowledge within the team. Implement best practices for security, including authentication, authorization, and data protection. Optimize applications for maximum speed and scalability. Maintain clear and comprehensive documentation for backend systems, APIs, and technical processes. Ensure version control systems (e.g., Git) are consistently updated and organized. Requirements Bachelors/master’s in computer science or computer engineering. Certifications in Python, Django, or cloud platforms are a plus. Skills Technical skills Proficiency in Python and Django framework. Strong understanding of RESTful API design and development. Experience with relational databases (PostgreSQL, MySQL) and ORMs like Django ORM. Knowledge of version control systems,particularly Git. Familiarity with Docker, Kubernetes, and containerized deployments. Exposure to cloud platforms such as AWS, Google Cloud, or Azure. Knowledge of caching systems like Redis or Memcached. Experience with CI/CD pipelines and automated deployments. Soft Skills Strong analytical and problem-solving skills. Excellent written and verbal communication abilities. Ability to work effectively in a collaborative, fast-paced environment. Eagerness to learn and adapt to new technologies. Show more