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customer engineer, data analytics, google cloud

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data analytics Jobs in Qatar Moph License Jobs In Qatar Moph License Jobs In Charge Jobs In Doha

data analytics

customer engineer data analytics google cloud

Google

<div><h3 class="jobSectionHeader">Minimum qualifications:</h3><ul>
<li>Bachelor's degree or equivalent practical experience.</li>
<li>10 years of experience with cloud native architecture in a customer-facing or support role.</li>
<li>Experience with &quot;Big Data&quot; technologies or concepts, such as analytics warehousing, data processing, data transformation, data governance, data migrations, ETL, ELT, SQL, NoSQL, performance or scalability optimizations, or batch versus streaming.</li>
<li>Experience with Data Warehousing architectures (e.g., legacy appliances like Teradata/Netezza or modern cloud warehouses).</li>
<li>Experience in SQL and data visualization tools (Looker, Tableau, Power BI).</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>Experience scripting in Python, Java, or Go for data processing tasks.</li>
<li>Experience presenting technical concepts to C-level executives and leading technical whiteboard sessions.</li>
<li>Experience architecting and deploying data solutions on public cloud platforms (Google Cloud).</li>
<li>Experience with Google Cloud BigQuery, Looker, and machine learning integration in data warehouses (e.g. BigQuery ML).</li>
<li>Understanding of the data analytics market, including current trends in business intelligence and big data.</li>
<li>Ability to explain data concepts to non-technical executive stakeholders, including familiarity with ETL/ELT pipelines and orchestration tools (e.g., Airflow/Cloud Composer, dbt).</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.
 
 
As a Customer Engineer, you will partner with technical Sales teams as a data analytics subject matter expert to differentiate Google Cloud to our customers. You will help prospective and existing customers and partners understand the power of Google Cloud, develop creative cloud solutions and architectures to solve their business issues, engage in proofs-of-concepts, and troubleshoot any technical questions and roadblocks related to database migrations, data back-ends and all aspects of the data life-cycle. You will engage with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. 
 
You will be a part of a various team of fellow Googlers working in an environment of respect where we promote equal opportunities to succeed.Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Collaborate with the team to identify and qualify business opportunities, understand key customer objections, and develop a strategy to resolve technical blockers in relation to aspects of the data life-cycle.</li>
<li>Share in-depth data analytics expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partnering directly with product management to prioritize solutions impacting customer adoption to Google Cloud.</li>
<li>Identify business and technical requirements, conduct full technical discovery and architect client solutions to meet gathered requirements.</li>
<li>Demonstrate and prototype integrations in customer and partner environments by working directly with Google Cloud products.</li>
<li>Prepare and deliver sales messaging in an effort to highlight the Google Cloud value proposition, using techniques such as whiteboard and slide presentations, product demonstrations, white papers and RFI responses.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Customer Engineer, Data Analytics, Google Cloud

<div>
 
 Minimum qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's degree or equivalent practical experience.
 </li>
 <li>
 10 years of experience with cloud native architecture in a customer-facing or support role.
 </li>
 <li>
 Experience with "Big Data" technologies or concepts, such as analytics warehousing, data processing, data transformation, data governance, data migrations, ETL, ELT, SQL, NoSQL, performance or scalability optimizations, or batch versus streaming.
 </li>
 <li>
 Experience with Data Warehousing architectures (e.g., legacy appliances like Teradata/Netezza or modern cloud warehouses).
 </li>
 <li>
 Experience in SQL and data visualization tools (Looker, Tableau, Power BI).
 
 
 </li>
 </ul>
 
 Preferred qualifications:
 
 
 
 <ul>
 <li>
 Experience scripting in Python, Java, or Go for data processing tasks.
 </li>
 <li>
 Experience presenting technical concepts to C-level executives and leading technical whiteboard sessions.
 </li>
 <li>
 Experience architecting and deploying data solutions on public cloud platforms (Google Cloud).
 </li>
 <li>
 Experience with Google Cloud BigQuery, Looker, and machine learning integration in data warehouses (e.g. BigQuery ML).
 </li>
 <li>
 Understanding of the data analytics market, including current trends in business intelligence and big data.
 </li>
 <li>
 Ability to explain data concepts to non-technical executive stakeholders, including familiarity with ETL/ELT pipelines and orchestration tools (e.g., Airflow/Cloud Composer, dbt).
 
 
 </li>
 </ul>
 
 About the job
 
 When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.
 
 
 As a Customer Engineer, you will partner with technical Sales teams as a data analytics subject matter expert to differentiate Google Cloud to our customers. You will help prospective and existing customers and partners understand the power of Google Cloud, develop creative cloud solutions and architectures to solve their business issues, engage in proofs-of-concepts, and troubleshoot any technical questions and roadblocks related to database migrations, data back-ends and all aspects of the data life-cycle. You will engage with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud.
 
 
 You will be a part of a various team of fellow Googlers working in an environment of respect where we promote equal opportunities to succeed.Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Collaborate with the team to identify and qualify business opportunities, understand key customer objections, and develop a strategy to resolve technical blockers in relation to aspects of the data life-cycle.
 </li>
 <li>
 Share in-depth data analytics expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partnering directly with product management to prioritize solutions impacting customer adoption to Google Cloud.
 </li>
 <li>
 Identify business and technical requirements, conduct full technical discovery and architect client solutions to meet gathered requirements.
 </li>
 <li>
 Demonstrate and prototype integrations in customer and partner environments by working directly with Google Cloud products.
 </li>
 <li>
 Prepare and deliver sales messaging in an effort to highlight the Google Cloud value proposition, using techniques such as whiteboard and slide presentations, product demonstrations, white papers and RFI responses.
 
 
 
 </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>

Codvo.ai

<div><div><div>Data Architect (Category - Architect)
Sector: Oil and Gas
Location: Doha, Qatar<div></div> 
About Us
At Codvo, we are committed to building scalable, future-ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting-edge technology. 
Our Vision: Engineering the Future of Energy with Data
Our digital transformation is moving from strategy to execution. We have a clear roadmap of high-impact data and AI use cases designed to fundamentally re-engineer our operations&mdash;from improving efficiency and implementing predictive maintenance on critical assets to enhancing subsurface modeling for better exploration outcomes. This is not just an IT upgrade; it is a core business imperative to create a more resilient, efficient, and intelligent energy company. We are now building the core team of innovators and builders to deliver these initiatives. This role is critical to bringing that vision to life, moving beyond theory to engineer the specific, robust data solutions that will power our most strategic projects and deliver measurable value. 
The Opportunity:
The Data Architect will be responsible for designing, governing, and evolving the organization&rsquo;s enterprise data architecture, ensuring that data platforms are scalable, secure, interoperable, and AI-ready. This role focuses on defining data models, integration patterns, governance standards, and architecture blueprints that enable analytics, AI, and digital products at scale.
The architect will work closely with data engineers, solution architects, cloud teams, business stakeholders, and cybersecurity teams to ensure data architecture aligns with business priorities and regulatory requirements. 
Job Description:
Key Responsibilities: 
Enterprise Data Architecture &amp; Design:<ul><li>Define and maintain the enterprise data architecture blueprint, including data lakes, warehouses, streaming platforms, and analytics layers.</li><li>Design logical, physical, and conceptual data models to support operational, analytical, and AI use cases.</li><li>Ensure architecture supports scalability, performance, and high availability.</li></ul> 
Cloud Data Platforms &amp; Integration:<ul><li>Architect cloud-native data platforms using Azure (ADF, Synapse, Databricks, Fabric) and/or GCP equivalents.</li><li>Design secure hybrid architectures integrating on-premises systems with cloud data platforms.</li></ul> 
 Data Governance, Quality &amp; Security:<ul><li>Define and enforce data governance frameworks, including metadata management, data lineage, data ownership, and stewardship models.</li><li>Establish data quality standards, validation rules, and monitoring mechanisms.</li><li>Ensure compliance with ISO 27001, NIA Qatar, data privacy, and internal cybersecurity policies.</li><li>Define data security architecture including encryption, access control, and role-based data access.</li></ul> 
 Analytics, AI &amp; Advanced Use Cases:<ul><li>Design data architectures that support advanced analytics, AI/ML, and digital twin initiatives.</li><li>Collaborate with data scientists and analysts to optimize data models for analytics and AI consumption.</li></ul> 
 Architecture Governance &amp; Leadership:<ul><li>Establish data architecture standards, reference architectures, and best practices.</li><li>Review solution designs to ensure alignment with enterprise data architecture principles.</li></ul> 
Required Skills and Qualifications:<ul><li> 
Bachelor&rsquo;s or master&rsquo;s degree in computer science, Data Engineering, Information Systems, or related field.</li><li>10+ years of experience in data architecture, data engineering, or enterprise analytics roles.</li><li>Strong experience designing enterprise-scale data platforms in cloud and hybrid environments.</li><li>Expertise in data modelling (conceptual, logical, physical) and data integration patterns.</li><li>Deep understanding of data lakes, data warehouses, Lakehouse architectures, and real-time streaming platforms.</li><li>Hands-on experience with cloud data services (Azure preferred).</li><li>Strong knowledge of SQL, data transformation frameworks, and metadata management.</li><li>Familiarity with DevOps and DataOps practices.</li><li>Strong communication skills with the ability to engage both technical and business stakeholders.</li></ul> 
Technical Proficiencies:<ul><li>Expert-level proficiency in SQL and Python for data manipulation and pipeline development.</li><li>Big Data Technologies: Hands-on experience with distributed computing frameworks like Apache Spark (PySpark). Experience with streaming technologies like Kafka is a plus.</li><li>Cloud Platforms: Deep experience with Microsoft Azure (Azure Data Lake Storage, Azure Data Factory, Azure Databricks, Azure Synapse).</li><li>Data Warehousing/Lakehouse: Proven experience with modern data platforms Databricks Delta Lake.</li><li>AI &amp; ML Knowledge: Understanding of machine learning lifecycles and the data requirements for training and deploying AI/ML models.</li><li>Orchestration: Experience with workflow orchestration tools like Airflow, Dagster, or Azure Data Factory.</li><li>Databases: Strong understanding of both relational (e.g., PostgreSQL, SQL Server) and NoSQL databases. Experience with graph databases (e.g., Neo4j) and vector databases is highly desirable.</li><li>Version Control: Proficiency with Git and CI/CD best practices.</li></ul> 
Preferred Qualifications:<ul><li>Certifications such as Azure Data Engineer Expert, Azure Solutions Architect, or equivalent.</li><li>Hands-on experience with the OSDU&trade; Data Platform.</li><li>Experience in Oil &amp; Gas, energy, or industrial data environments.</li><li>Understanding of cybersecurity considerations for OT environments and data segregation.</li><li>Experience integrating data from ERP systems like SAP.</li><li>Experience working within AI-first or analytics-driven transformation programs.</li><li>Advanced SQL skills, including query optimization and performance tuning.</li><li>Knowledge of containerization technologies (Docker, Kubernetes).</li><li>Experience of constructing and maintaining enterprise knowledge graphs.</li></ul></div></div></div>

Data Architect (Category - Architect) (Doha)

Madre Integrated Engineering

<div>
 
 Gigamon Engineer
 
 
 Role overview
 
 
 A Gigamon Engineer is responsible for designing, deploying, and operating Gigamon
 
 
 visibility/packet broker platforms that provide traffic to security, monitoring, and
 
 
 performance tools in enterprise or service provider networks. The role often includes
 
 
 acting as a subject matter expert to optimize traffic flows, filters, and policies for security
 
 
 and NOC teams.
 
 
 Key responsibilities
 
 
  Design and implement Gigamon visibility solutions, including GigaVUE nodes,
 
 
 cluster design, and integration with core, data center, and cloud networks.
 
 
  Configure and manage flow maps, filters, load balancing, deduplication, header
 
 
 stripping, and SSL/TLS decryption as required by security and monitoring tools.
 
 
  Integrate Gigamon with IDS/IPS, firewalls, SIEM, APM/NPM, and other analytics
 
 
 platforms, ensuring the right traffic reaches the right tools without
 
 
 oversubscription.
 
 
  Monitor platform health, capacity, and performance; plan upgrades, patches, and
 
 
 expansions in coordination with network and security teams.
 
 
  Troubleshoot packetlevel issues, visibility gaps, and tool performance problems
 
 
 using SPAN/TAPs, Gigamon nodes, and protocol analyzers like Wireshark.
 
 
  Create and maintain design documents, runbooks, and standard operating
 
 
 procedures for Gigamon operations.
 
 
  Provide knowledge transfer, training, and advisory support to customer or internal
 
 
 teams on best practices for traffic visibility and usecase design.
 
 
 Required skills and experience
 
 
  Strong background in enterprise or data center networking (routing, switching,
 
 
 VLANs, trunks, SPAN, TAPs, L2/L3 protocols).
 
 
  Handson experience with Gigamon visibility appliances (e.g., GigaVUE series)
 
 
 including clustering, management (H/Vision), and advanced traffic policies.
 
 
  Familiarity with security and monitoring tools (IDS/IPS, firewalls, WAF, DLP,
 
 
 NPM/APM, SIEM) and how they consume mirrored traffic.
 
</div>

Gigamon Engineer

Canonical

<div>
 Canonical is a leading provider of open source software and operating systems to the global enterprise and technology markets. Our platform, Ubuntu, is very widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation and IoT. Our customers include the world's leading public cloud and silicon providers, and industry leaders in many sectors. The company is a pioneer of global distributed collaboration, with 1000+ colleagues in 70+ countries and very few roles based in offices. Teams meet two to four times yearly in person, in interesting locations around the world, to align on strategy and execution.
 
 
 The company is founder led, profitable and growing. We are hiring
 
 Python and Kubernetes Specialist Engineers focused on Data, Workflows, AI/ML and Analytics Solutions
 
 to join our teams building open source solutions for public cloud and private infrastructure.
 
 
 As a software engineer on the team, you'll collaborate on end-to-end data analytics and MLOps solutions composed of popular, open-source, machine learning tools, such as Kubeflow, MLFlow, DVC, and Feast. You may also work on ETL, data governance and visualization tools like Apache SuperSet, dbt, workflow orchestration tools such as Airflow and Temporal, or data warehouse solutions such as Apache Trino, or ClickHouse. These solutions may be run on servers or on the cloud, on machines or on Kubernetes, on developer desktops, or as web services.
 
 
 We serve the needs of individuals and community members as much as the needs of our Global 2000 and Fortune 500 customers; we make our primary work available free of charge and our Pro subscriptions are also available to individuals for personal use at no cost. Our goal is to enable more people to enjoy the benefits of open source, regardless of their circumstances.
 
 
 
 Location:
 
 This initiative spans many teams that are home-based and in multiple time zones. We believe in distributed collaboration but we also try to ensure that colleagues have company during their work hours! Successful candidates will join a team where most members and your manager are broadly in the same time zone so that you have the benefits of constant collaboration and discussion.
 
 
 
 What your day will look like
 
 
 
 <ul>
 <li>
 Develop your understanding of the entire Linux stack, from kernel, networking, and storage, to the application layer
 </li>
 <li>
 Design, build and maintain solutions that will be deployed on public and private clouds and local workstations
 </li>
 <li>
 Master distributed systems concepts such as observability, identity, tracing
 </li>
 <li>
 Work with both Kubernetes and machine-oriented open source applications
 </li>
 <li>
 Collaborate proactively with a distributed team of engineers, designers and product managers
 </li>
 <li>
 Debug issues and interact in public with upstream and Ubuntu communities
 </li>
 <li>
 Generate and discuss ideas, and collaborate on finding good solutions
 
 
 </li>
 </ul>
 
 What we are looking for in you
 
 
 
 <ul>
 <li>
 Professional or academic software delivery using Python
 </li>
 <li>
 Exceptional academic track record from both high school and university
 </li>
 <li>
 Undergraduate degree in a technical subject or a compelling narrative about your alternative chosen path
 </li>
 <li>
 Confidence to respectfully speak up, exchange feedback, and share ideas without hesitation
 </li>
 <li>
 Track record of going above-and-beyond expectations to achieve outstanding results
 </li>
 <li>
 Passion for technology evidenced by personal projects and initiatives
 </li>
 <li>
 The work ethic and confidence to shine alongside motivated colleagues
 </li>
 <li>
 Professional written and spoken English with excellent presentation skills
 </li>
 <li>
 Experience with Linux (Debian or Ubuntu preferred)
 </li>
 <li>
 Excellent interpersonal skills, curiosity, flexibility, and accountability
 </li>
 <li>
 Appreciative of diversity, polite and effective in a multi-cultural, multi-national organisation
 </li>
 <li>
 Thoughtfulness and self-motivation
 </li>
 <li>
 Result-oriented, with a personal drive to meet commitments
 </li>
 <li>
 Ability to travel twice a year, for company events up to two weeks long
 
 
 </li>
 </ul>
 
 Additional skills that would be nice to have
 
 
 
 The following skills may be helpful to you in the role, but we don't expect everyone to bring all of them.
 
 
 <ul>
 <li>
 Proven track record of building highly automated machine learning solutions, data pipelines, or orchestrating workflows for the cloud.
 </li>
 <li>
 Hands-on experience with machine learning libraries, or tools.
 </li>
 <li>
 Experience with container technologies (Docker, LXD, Kubernetes, etc.)
 </li>
 <li>
 Experience with public clouds (AWS, Azure, Google Cloud)
 </li>
 <li>
 Working knowledge of cloud computing
 </li>
 <li>
 Passionate about software quality and testing
 </li>
 <li>
 Experience working on an open source project
 
 
 </li>
 </ul>
 
 What we offer colleagues
 
 
 
 We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually (and more often for graduates and associates) to ensure we recognise outstanding performance. In addition to base pay, we offer a performance-driven annual bonus or commission. We provide all team members with additional benefits, which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally.
 
 
 <ul>
 <li>
 Distributed work environment with twice-yearly team sprints in person
 </li>
 <li>
 Personal learning and development budget of USD 2,000 per year
 </li>
 <li>
 Annual compensation review
 </li>
 <li>
 Recognition rewards
 </li>
 <li>
 Annual holiday leave
 </li>
 <li>
 Maternity and paternity leave
 </li>
 <li>
 Employee Assistance Programme
 </li>
 <li>
 Opportunity to travel to new locations to meet colleagues
 </li>
 <li>
 Priority Pass, and travel upgrades for long haul company events
 
 
 </li>
 </ul>
 
 About Canonical
 
 
 
 Canonical is a pioneering tech firm at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT and the cloud, we are changing the world of software. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence - in order to succeed, we need to be the best at what we do. Most colleagues at Canonical have worked from home since its inception in 2004. Working here is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game.
 
 
 
 Canonical is an equal opportunity employer
 
 
 
 We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration.
 
 
</div>

Python and Kubernetes Software Engineer - Data, Workflows, AI/ML & Analytics

TAT IT Technolgies

<div>
 
 We have an urgent requirement for Machine Learning Engineer for our client based in Qatar
 
 
 
 
 Develop and implement machine learning models and algorithms to derive insights, predictions, and recommendations from Labour-related data.--
 
 
 -Must
 
 
 
 
 Strong proficiency in programming languages such as Python, R, or Java, with expertise in machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch)---
 
 
 Must
 
 
 
 
 deep learning algorithms, neural networks, and convolutional/recurrent architectures.---
 
 
 Must
 
 
 
 
 integrate machine learning models into the LMIS infrastructure, including data pipelines and real-time prediction systems.--
 
 
 Must
 
 
 
 
 Background
 
 
 
 
 Client is seeking a skilled and experienced Machine Learning Engineer to contribute to the development and implementation of a Labour Market Information System (LMIS). The LMIS aims to leverage machine learning algorithms and techniques to automate processes, make predictions, and generate actionable insights. The selected Machine Learning Engineer will play a key role in designing, developing, and deploying machine learning models within the LMIS.
 
 
 
 
 Objectives
 
 
 
 The main objectives of the Machine Learning Engineer are as follows:
 
 
 <ul>
 <li>
 Develop and implement machine learning models and algorithms to derive insights, predictions, and recommendations from Labour-related data.
 </li>
 <li>
 Collaborate with the Data Engineering team to ensure the availability, quality, and preprocessing of data for training and validation purposes.
 </li>
 <li>
 Optimize and fine-tune machine learning models to improve accuracy, performance, and efficiency.
 </li>
 <li>
 Deploy machine learning models within the LMIS infrastructure to enable real-time predictions and analysis.
 </li>
 <li>
 Continuously monitor and evaluate model performance, incorporating feedback and iterative improvements.
 </li>
 <li>
 Stay updated with the latest advancements in machine learning, deep learning, and AI to propose innovative solutions and enhance the LMIS.
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 The Machine Learning Engineer will be responsible for the following tasks:
 
 
 <ul>
 <li>
 Collaborate with stakeholders to understand business requirements and identify opportunities for applying machine learning techniques.
 </li>
 <li>
 Perform data preprocessing, feature engineering, and data augmentation to prepare the data for machine learning model development.
 </li>
 <li>
 Develop, implement, and validate machine learning models, including supervised and unsupervised learning algorithms, regression models, and classification models.
 </li>
 <li>
 Optimize models for scalability, performance, and interpretability while ensuring compliance with data privacy and security standards
 </li>
 <li>
 Collaborate with the Data Engineering team to integrate machine learning models into the LMIS infrastructure, including data pipelines and real-time prediction systems.
 </li>
 <li>
 Conduct regular evaluations and model performance monitoring, making necessary adjustments and retraining as needed.
 </li>
 <li>
 Implement version control and documentation processes to maintain model versions and track changes.
 </li>
 <li>
 Collaborate with stakeholders to interpret and present model outputs, insights, and recommendations in a meaningful and actionable manner.
 </li>
 <li>
 Ensure compliance with ethical considerations and legal requirements in the use of machine learning algorithms and data.
 
 
 </li>
 </ul>
 
 Qualifications And Skills
 
 
 
 The ideal candidate should possess the following qualifications and skills:
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
 </li>
 <li>
 Proven experience (at least 3 years) in machine learning model development, implementation, and deployment.
 </li>
 <li>
 Strong proficiency in programming languages such as Python, R, or Java, with expertise in machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
 </li>
 <li>
 Experience with data preprocessing, feature engineering, and data augmentation techniques.
 </li>
 <li>
 Understanding of various machine learning algorithms, including supervised and unsupervised learning, regression, and classification.
 </li>
 <li>
 Familiarity with deep learning algorithms, neural networks, and convolutional/recurrent architectures.
 </li>
 <li>
 Knowledge of model evaluation metrics, cross-validation techniques, and hyperparameter tuning.
 </li>
 <li>
 Experience with model deployment and integration in production environments using frameworks like Flask or Docker.
 </li>
 <li>
 Familiarity with cloud platforms and services for scalable model deployment (e.g., AWS, Azure, Google Cloud).
 </li>
 <li>
 Strong problem-solving skills and ability to translate business requirements into machine learning solutions.
 </li>
 <li>
 Excellent communication and collaboration skills to work effectively with stakeholders and contribute to a multidisciplinary team
 
 
 </li>
 </ul>
 
 Deliverables
 
 
 
 The Machine Learning Engineer will be responsible for delivering the following key outputs:
 
 
 <ul>
 <li>
 Developed and validated machine learning models for Labour-related insights, predictions,
 
 
 </li>
 </ul>
 and recommendations.
 
 
 <ul>
 <li>
 Integrated machine learning models into the LMIS infrastructure for real-time predictions.
 </li>
 <li>
 Regular model evaluations and performance monitoring reports.
 </li>
 <li>
 Documentation of machine learning processes, model versions, and deployment procedures
 
 
 </li>
 </ul>
 Skills: machine learning,algorithms,learning
</div>

Machine Learning Engineer

QatarEnergy

<div>
 
 Primary Purpose Of The Job
 
 
 
 Responsible for leading the Offensive red teaming activities on QatarEnergy&rsquo;s IT/OT environments, by conducting threat hunting, penetration testing, Vulnerability scanning and security assurance activities. Provides oversight and technology guidance as well as managerial support as required. Oversee the execution of incident management program and supervises and coordinates engineers and external consultants to design, build and manage QatarEnergy SOC Red team functions on QatarEnergy&rsquo;s IT and OT cyber security mission critical operational expansion.
 
 
 
 Required Experience And Skills
 
 
 
 <ul>
 <li>
 Strong understanding of cyber incident management, malware management and vulnerability management processes.
 </li>
 <li>
 Solid knowledge on Malware analysis, Vulnerability assessment &amp; Forensic &amp; memory analysis, and data analytics
 </li>
 <li>
 Experience with large ICS &amp; ICT environments in the Energy sector is a big plus.
 </li>
 <li>
 Advanced knowledge of networking fundamentals (TCP/IP, network layers, Ethernet, etc) Advanced knowledge of current threat landscape (threat actors, APT, cyber-crime, etc) Advanced knowledge of penetration techniques and forensic techniques. Protocol analysis knowledge and experience (Wireshark, Netwitness, etc.) Solid knowledge of client-server applications, multi-tier web applications, relational databases.
 </li>
 <li>
 Solid knowledge and experience with Cloud technologies (Amazon, Azure, Google Cloud, IaaS, SaaS etc.)
 </li>
 <li>
 Good knowledge of IT including multiple operating systems and system administration skills (Windows, Unix)
 </li>
 <li>
 Solid understanding of IT governance and processes, such as ITIL, COBIT.
 </li>
 <li>
 Possession of Industry Certifications ISACA, GCIA, SANS, ICS2, EC-Council, other relevant cyber security certifications. (such as CISSP, CISM, (GCIH), (GIAC), (CEH), (CEPT), OSCE, CHFI, GREM or equivalent security technologies technical certification (Advanced Level)
 </li>
 <li>
 Must maintain professional demeanor in stressful situations.
 
 
 </li>
 </ul>
 
 Educational Qualifications
 
 
 
 Bachelor&rsquo;s degree in information security, computer science, or systems engineering. 10+ years of technical experience in Information Security, System Administration, or Network Engineering with at least 5 years of experience in Information Security.
</div>

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1342 customer engineer data analytics google cloud jobs IN Qatar Moph License Jobs In Qatar Moph License Jobs In Charge Jobs In Doha

Customer Engineer, Data Analytics, Google Cloud

Customer Engineer, Data Analytics, Google Cloud

Data Architect (Category - Architect) (Doha)

Gigamon Engineer

Python and Kubernetes Software Engineer - Data, Workflows, AI/ML & Analytics

Machine Learning Engineer

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