ai engineer

bd engineer

data analyst

data scientist

data scientist (ami)

data engineer

Confidential

Role Overview: Design and manage scalable data infrastructure to support operational and analytical systems. Key Responsibilities:<ul><li>Build and maintain data pipelines and architectures</li><li>Ensure data quality, performance, and availability</li><li>Support real-time and batch data processing</li><li>Collaborate with IT, security, and operations teams</li></ul> Requirements:<ul><li>Degree in Computer Science / IT or related</li><li>8–10+ years in data engineering</li><li>Strong experience with databases and big data technologies</li></ul>

Infrastructure Data Engineer

<div>
 
 Overview
 
 
 
 
 
 We are seeking a Senior ETL Designer &amp; Developer to design, build, and support enterprise-scale data integration and analytics solutions across Informatica PowerCenter, Teradata EDW, and Google Cloud Platform (GCP). The role involves developing scalable ETL pipelines, enabling telecom data processing, supporting enterprise reporting (including ad-hoc analytics), and optimizing large-scale EDW environments.
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 ETL &amp; Data Engineering
 
 <ul>
 <li>
 Design, develop, and maintain ETL/ELT workflows using Informatica PowerCenter
 </li>
 <li>
 Build scalable batch and near real-time data pipelines
 </li>
 <li>
 Develop reusable mappings, workflows, and transformation logic
 </li>
 <li>
 Automate ETL processes using Unix shell scripting
 </li>
 </ul>
 
 Data Warehouse (Teradata)
 
 <ul>
 <li>
 Work extensively with Teradata Enterprise Data Warehouse environments
 </li>
 <li>
 Strong experience with Teradata CLDM (Common Logical Data Model)
 </li>
 <li>
 Design and manage EDW layered architecture (Staging, ODS, EDW, Data Marts)
 </li>
 <li>
 Extensive expertise in Teradata performance optimization techniques including: Explain plan analysis, Partitioning strategies, Join/index optimization (PI, NUSI, etc.), Query tuning and workload management
 </li>
 <li>
 Strong Teradata SQL coding expertise for complex transformations and large datasets
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 Design and optimize dimensional models (star/snowflake schemas)
 </li>
 </ul>
 
 Cloud Data Engineering
 
 <ul>
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 Develop solutions on Google Cloud Platform (BigQuery, Dataflow, Cloud Storage, Pub/Sub)
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 <li>
 Implement and support hybrid data architectures integrating on-prem EDW with cloud systems
 </li>
 </ul>
 
 BI, Reporting &amp; Data Virtualization
 
 <ul>
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 Support enterprise BI tools: SAP BusinessObjects, Qlik Sense, Looker
 </li>
 <li>
 Support ad-hoc reporting requirements from business users using EDW and BI layers
 </li>
 <li>
 Work with Denodo Platform for federated data access, performance optimization, and logical data modeling
 </li>
 </ul>
 
 Telecom Domain Experience
 
 <ul>
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 Strong experience in telecom OSS/BSS data environments
 </li>
 <li>
 Hands-on knowledge of: CDR/IPDR data processing; Billing, CRM, and subscriber lifecycle data; Network performance, fault, and mediation systems
 </li>
 <li>
 Understanding of telecom KPIs (ARPU, churn, usage patterns, QoS metrics)
 </li>
 <li>
 Experience handling high-volume, complex telecom datasets
 </li>
 </ul>
 
 Scripting &amp; Performance Optimization
 
 <ul>
 <li>
 Strong expertise in Unix shell scripting for automation, scheduling, and monitoring
 </li>
 <li>
 Advanced Teradata performance tuning and optimization for large-scale workloads
 </li>
 <li>
 Optimize ETL jobs, SQL queries, and EDW processes for scalability and efficiency
 </li>
 <li>
 Troubleshoot pipeline failures and ensure system reliability
 </li>
 </ul>
 
 Required Skills
 
 <ul>
 <li>
 7+ years of experience in ETL development and data warehousing
 </li>
 <li>
 Strong hands-on experience with Informatica PowerCenter
 </li>
 <li>
 Deep expertise in Teradata EDW, including CLDM and optimization techniques
 </li>
 <li>
 Strong Teradata SQL coding and performance tuning skills
 </li>
 <li>
 Experience with EDW architecture (Staging, ODS, EDW, Data Marts)
 </li>
 <li>
 Advanced SQL and data modeling (Kimball/Inmon)
 </li>
 <li>
 Experience with Google Cloud Platform data services
 </li>
 <li>
 Unix shell scripting for automation
 </li>
 <li>
 Telecom domain experience (preferred/required based on role level)
 </li>
 </ul>
 
 Preferred Skills
 
 <ul>
 <li>
 Cloud migration experience (on-prem EDW to GCP)
 </li>
 <li>
 Python or additional scripting/automation skills
 </li>
 <li>
 CI/CD pipelines for data engineering workflows
 </li>
 <li>
 Experience with BI semantic layers and enterprise reporting frameworks
 </li>
 <li>
 Experience supporting ad-hoc business reporting in enterprise environments
 </li>
 </ul>
 
 Soft Skills
 
 <ul>
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 Strong communication and stakeholder management skills
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 <li>
 Analytical thinking and strong problem-solving ability
 </li>
 <li>
 Ability to work in agile, fast-paced environments
 </li>
 <li>
 Strong ownership mindset with focus on data quality and delivery
 </li>
 </ul>
</div>

Senior ETL Designer & Developer

malomatia

<div>
 
 Job Description
 
 
 
 Must Have
 
 
 <ul>
 <li>
 3&ndash;5 years of experience in data science, analytics, or a quantitative modeling role.
 </li>
 <li>
 Hands-on proficiency in Python (pandas, NumPy, scikit-learn) and SQL for building and evaluating models end to end.
 </li>
 <li>
 Demonstrated ability to design experiments, validate model performance, and guard against overfitting and data leakage.
 </li>
 <li>
 Clear, reproducible, and well-documented analytical practice.
 </li>
 <li>
 Ability to communicate findings clearly to both technical colleagues and business stakeholders.
 
 
 </li>
 </ul>
 Nice to Have
 
 
 <ul>
 <li>
 Experience with visualization tools such as matplotlib, seaborn, Power BI, or Tableau.
 </li>
 <li>
 Exposure to cloud analytics environments, ideally Oracle Cloud Infrastructure (OCI).
 </li>
 <li>
 Experience with time-series analysis or natural-language data.
 </li>
 <li>
 Familiarity with collaborative workflows and code review.
 </li>
 <li>
 Exposure to working with engineering teams on model handoff.
 </li>
 <li>
 Data science certifications.
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Conduct exploratory data analysis to uncover patterns, relationships, and opportunities in client and operational data.
 </li>
 <li>
 Build, train, and evaluate predictive and descriptive models using Python (pandas, scikit-learn) and SQL.
 </li>
 <li>
 Build and evaluate deep learning models, such as neural networks, using frameworks like TensorFlow or PyTorch where they suit the problem.
 </li>
 <li>
 Perform feature engineering, data cleaning, and dataset preparation for modeling.
 </li>
 <li>
 Design and analyze experiments, including A/B tests, to measure the impact of changes and interventions.
 </li>
 <li>
 Prototype analytical solutions and iterate on them based on stakeholder and senior data scientist feedback.
 </li>
 <li>
 Create clear visualizations, dashboards, and summaries that translate analysis into business insight.
 </li>
 <li>
 Validate model performance using appropriate metrics and guard against overfitting and data leakage.
 </li>
 <li>
 Document methodology, assumptions, and results to ensure reproducibility and knowledge sharing.
 </li>
 <li>
 Collaborate with senior data scientists, engineers, and analysts on larger initiatives.
 </li>
 <li>
 Support the preparation of analytical reports and presentations for clients and internal teams.
 </li>
 <li>
 Maintain and improve existing analytical code and notebooks
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in a quantitative field (Statistics, Mathematics, Computer Science, Engineering, Data Science) or equivalent experience; Master's an advantage.
 </li>
 <li>
 Proficiency in Python for data analysis (pandas, NumPy, scikit-learn) and working knowledge of SQL.
 </li>
 <li>
 Solid grounding in statistics and core machine-learning techniques (regression, classification, clustering).
 </li>
 <li>
 Working knowledge of deep learning concepts and frameworks such as TensorFlow or PyTorch.
 </li>
 <li>
 Experience with feature engineering and preparing real-world, messy datasets for modeling.
 </li>
 <li>
 Ability to communicate findings clearly to technical and business audiences.
 </li>
 <li>
 Understanding of model evaluation metrics and validation techniques.
 </li>
 <li>
 Familiarity with version control (Git) and reproducible analysis practices.
 </li>
 </ul>
</div>

Data Scientist

Inspire Management Training Center

,artificialThe Data Scientist (AMI) is responsible for analyzing smart meter and energy consumption data from Advanced Metering Infrastructure systems to generate actionable insights for utility operations. The role focuses on predictive analytics, anomaly detection, forecasting, and optimization of energy usage, supporting data-driven decision-making, operational efficiency, and smart grid improvements.Job Responsibilities<ul><li>Analyze large volumes of AMI smart meter data to identify trends, patterns, and anomalies.</li><li>Develop predictive models for energy consumption, load forecasting, and outage detection.</li><li>Perform data cleaning, transformation, and feature engineering on AMI datasets.</li><li>Build and deploy statistical and machine learning models to support utility operations.</li><li>Detect meter faults, non-technical losses (NTL), and abnormal consumption behavior.</li><li>Develop dashboards, reports, and visualizations to communicate insights to stakeholders.</li><li>Collaborate with AMI engineers, data engineers, and business teams to define analytics requirements.</li><li>Support Meter Data Management System (MDMS) analytics and data validation processes.</li><li>Optimize algorithms for scalability and real-time or near real-time analytics.</li><li>Ensure data quality, governance, and compliance with utility and regulatory standards.</li></ul>Qualifications<ul><li>Master&rsquo;s or PHD in Data Science, AI, Computer Science or related field.</li><li>Certified in advanced data science, machine learning or artifical intelligence</li><li>Minimum 13 years of experience in data science, or advanced analytics, preferably in utlities or energy sector</li><li>Strong knowledge of machine learning, statistical modeling, and data mining techniques.</li><li>Proficiency in Python or R and data libraries such as Pandas, NumPy, Scikit-learn.</li><li>Experience with SQL and handling large-scale datasets.</li><li>Familiarity with AMI systems, smart metering, or energy utilities is preferred.</li><li>Experience with visualization tools such as Power BI, Tableau, or similar.</li></ul>Education:<ul><li>Doctorate (Required)</li></ul>Experience:<ul><li>Data Scientist: 10 years (Required)</li></ul>License/Certification:<ul><li>Advanced Data Science, machine learning, or AI (Required)</li></ul>Location:<ul><li>Doha (Required)</li></ul>Work Location: In person

Data Scientist (AMI)

<div>
 
 Job Description
 
 
 
 Must Have
 
 
 <ul>
 <li>
 4+ years of software or machine-learning engineering experience, including hands-on experience deploying models to production.
 </li>
 <li>
 Demonstrated track record operationalizing models developed by data scientists into reliable, scalable, and observable production systems.
 </li>
 <li>
 Production experience with classical machine-learning workloads &mdash; distinct from generative-AI application development.
 </li>
 <li>
 Strong collaboration skills across data science, software engineering, and platform teams.
 </li>
 <li>
 Commitment to building reliable, well-engineered, and maintainable systems.
 
 
 </li>
 </ul>
 Nice to Have
 
 
 <ul>
 <li>
 Experience with feature stores and large-scale or streaming data pipelines.
 </li>
 <li>
 Knowledge of infrastructure-as-code (e.g., Terraform) and cloud cost optimization.
 </li>
 <li>
 Experience with workflow orchestration tools (e.g., Apache Airflow).
 </li>
 <li>
 Familiarity with model-serving frameworks and API design for inference.
 </li>
 <li>
 Light exposure to generative-AI or LLM deployment.
 </li>
 <li>
 Experience operating systems in a regulated or enterprise environment.
 </li>
 <li>
 Cloud or MLOps certifications.
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Build, deploy, and maintain production machine-learning pipelines, from data ingestion and feature processing through to model serving.
 </li>
 <li>
 Operationalize models developed by data scientists, ensuring reliability, scalability, reproducibility, and performance.
 </li>
 <li>
 Implement MLOps practices including CI/CD for machine learning, model versioning, automated retraining, and model registries.
 </li>
 <li>
 Design and maintain feature pipelines and, where relevant, feature stores.
 </li>
 <li>
 Set up monitoring and alerting for model performance, data drift, and system health, and respond to degradation.
 </li>
 <li>
 Optimize inference latency, throughput, and resource cost for deployed models.
 </li>
 <li>
 Containerize and orchestrate machine-learning workloads using Docker and Kubernetes on Oracle Cloud Infrastructure (OCI).
 </li>
 <li>
 Automate and harden data and model workflows to reduce manual intervention.
 </li>
 <li>
 Collaborate with data scientists on model handoff, packaging, and success metrics.
 </li>
 <li>
 Work with software engineers to integrate models into client-facing applications and services.
 </li>
 <li>
 Apply software-engineering best practices including testing, code review, and documentation to machine-learning systems.
 </li>
 <li>
 Troubleshoot and resolve production issues across the model-serving stack.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Software Engineering, or a related field; equivalent experience accepted.
 </li>
 <li>
 Strong Python engineering skills and production experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch.
 </li>
 <li>
 Hands-on experience with MLOps tooling (e.g., MLflow, Kubeflow) and CI/CD pipelines.
 </li>
 <li>
 Proficiency with containerization and orchestration (Docker, Kubernetes).
 </li>
 <li>
 Experience building and maintaining data pipelines and processing large datasets.
 </li>
 <li>
 Experience with cloud infrastructure, ideally Oracle Cloud Infrastructure (OCI) and OCI Data Science.
 </li>
 <li>
 Understanding of model monitoring, drift detection, and retraining strategies.
 </li>
 <li>
 Solid software-engineering fundamentals including testing and version control.
 </li>
 </ul>
</div>

ML Engineer

Mergers United

As a Full Stack Software Engineer, the employee will be responsible for developing and maintaining both the frontend and backend of the company&rsquo;s digital platform using a modern full-stack web framework, React-based user interfaces, responsive styling tools, form validation, data fetching, rich-text editing, animations, drag-and-drop functionality, and PDF generation features. The role also includes working with cloud-based backend services such as authentication, databases, file storage, server-side functions, hosting, deployment pipelines, automated testing, and code quality tools. The employee will contribute to building secure, scalable, high-performance, and maintainable software while following best practices in data protection, application security, documentation, and collaboration with the company&rsquo;s business and technical teams.Job Type: Full-timePay: QAR4,000.00 - QAR6,000.00 per monthApplication Question(s):<ul><li>Which code language do you have most experience and how long did you work with this code language?</li></ul>Education:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>Full stack engineering or equal : 8 years (Required)</li></ul>Language:<ul><li>Arabic (Preferred)</li><li>English (Preferred)</li></ul>License/Certification:<ul><li>Microsoft Certified: Azure Developer Associate (AZ-204) (Preferred)</li><li>AWS Certified Developer - Associate Level (Preferred)</li><li>Google Cloud Certified - Professional Cloud Developer (Preferred)</li><li>PMP: Certified Associate in Project Management (Preferred)</li></ul>

Full Stack Software Engineer

We are hiring a Quantity Surveyor for a short-term project in Qatar. The candidate will prepare pre- and post-contract documents, evaluate variations and progress claims, provide commercial and contract guidance, monitor project progress, and assist in project and risk management. Candidates should hold a B.Sc. in Quantity Surveying or a related engineering discipline with RICS chartered status, and have a minimum of 5 years&rsquo; experience in consultancy or client-side project management.Nature and Scope of Position / Responsibilities:<ul><li>Preparation of the pre-contract documents such as Preliminary Estimating, Cost Planning, Bill of Quantities, Tender Documents (for all disciplines such as Civil, MEP, Systems) ... etc.</li><li>Evaluation of Post Contract documents such as Interim Valuations, Final Account, Claims Managements, Valuing Variations ... etc.</li><li>Provide the advice to project staff on commercial and contract matters including reviewing and drafting the contract correspondences.</li><li>Performing the jobs related to taking off the quantities for the purpose of certifying the progress claims &amp; variations.</li><li>Preparation of the bi-weekly reports on financial status of the projects including the projects cash flow forecast.</li><li>Monitor the progress of the projects in accordance with construction program and certify the progress claims accordingly.</li><li>Assist the Head of Civil and Landscape Section &amp; Technical Manager in Project management, Risk management, Contract management, Resolution of contract disputes ... etc.</li><li>Evaluation of the variations and negotiating the variation with the contractors and recommending to Section Heads and Technical Manager.</li></ul>Experience and Education:<ul><li>B.Sc. in Quantity Surveying from a reputable university OR B.Sc. in any engineering discipline from a reputable university as well as the candidate has to be Charted Engineer (from RICS).</li><li>Minimum of 5 years experience as a quantity surveyor in a reputed consultancy firm or as a client's rep.</li><li>Fluency in writing, reading and speaking English language is mandatory.</li><li>Excellency in computer skills including using MS Word and Excel, Internet browsing/searching, data transferring, making reports with good formatting ... etc.</li><li>Knowledge on contract management software such as &quot;Primavera P3&quot; MS Projects is preferred.</li></ul>Job Types: Full-time, TemporaryApplication Question(s):<ul><li>Do you have a B.Sc. in Quantity Surveying or a related engineering degree?</li><li>Are you a RICS Chartered Engineer?</li></ul>Experience:<ul><li>Quantity Surveyor: 5 years (Required)</li></ul>Language:<ul><li>English (Required)</li></ul>Location:<ul><li>Doha (Required)</li></ul>Work Location: In person

Quantity Surveyor

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