167 Data Professionals jobs in Doha

The Principal Data Engineer handles the design, development, and maintenance of data pipelines, ETL processes, and database management to support AI and data science initiatives. This role involves ensuring data quality, scalability, and performance across all data engineering activities.

• Design, develop, and maintain data pipelines, ETL processes, and database systems to support AI and data science initiatives.
• Collaborate with data scientists, AI/ML engineers, and other stakeholders to understand data requirements and ensure data availability and quality.
• Implement data governance, security, and regulatory standards in all data engineering activities.
• Optimize data pipelines and processes for scalability, performance, and cost-efficiency.
• Monitor and ensure the performance and reliability of data systems, identifying and resolving issues as needed.
• Stay updated with the latest advancements in data engineering technologies and best practices.
• Mentor and provide guidance to junior data engineers and other team members.
• Prepare and present data engineering reports and documentation to senior management and stakeholders.
• Participate in project planning and contribute to the development of project timelines and deliverables.
• Perform other duties relevant to the job as assigned by the Head of Data & AI Engineering or senior management.

• Bachelor’s degree in Data Engineering, Computer Science, or a related field.
• Relevant certifications (e.g., Google Cloud Professional Data Engineer, AWS Certified Big Data – Specialty) are preferred.
• Minimum of 8 years of experience in data engineering or related fields.
• Experience in designing and implementing data pipelines, ETL processes, and database systems for AI or technology-focused products.
• Strong programming skills in languages such as Python, SQL.
• Proficiency in data engineering tools and frameworks (e.g., Apache Spark, Kafka).
• Excellent problem-solving and analytical skills.
• Strong communication and interpersonal skills.
• Attention to detail and commitment to quality.
• In-depth understanding of data engineering principles, ETL processes, and database management.
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services.
• Knowledge of data governance, security, and regulatory standards.
• Ability to manage multiple tasks and prioritize effectively.
• Ability to work independently and as part of a team.

The Sr. Data Engineer supports the design, development, and maintenance of data pipelines, ETL processes, and database systems to support AI and data science initiatives. This role involves ensuring data quality, scalability, and performance across all data engineering activities.

1. Support the design, development, and maintenance of data pipelines, ETL processes, and database systems to support AI and data science initiatives.
2. Collaborate with data scientists, AI/ML engineers, and other stakeholders to understand data requirements and ensure data availability and quality.
3. Implement data governance, security, and regulatory standards in all data engineering activities.
4. Optimize data pipelines and processes for scalability, performance, and cost-efficiency.
5. Monitor and ensure the performance and reliability of data systems, identifying and resolving issues as needed.
6. Stay updated with the latest advancements in data engineering technologies and best practices.
7. Mentor and provide guidance to junior data engineers and other team members.
8. Prepare and present data engineering reports and documentation to senior management and stakeholders.
9. Participate in project planning and contribute to the development of project timelines and deliverables.
10. Perform other duties relevant to the job as assigned by the Principal Data Engineer or senior management.

• Bachelor’s degree in Data Engineering, Computer Science, or a related field.
• Relevant certifications (e.g., Google Cloud Professional Data Engineer, AWS Certified Big Data – Specialty) are preferred.
• Minimum of 5 years of experience in data engineering or related fields.
• Experience in designing and implementing data pipelines, ETL processes, and database systems for AI or technology-focused products.
• Strong programming skills in languages such as Python, SQL.
• Proficiency in data engineering tools and frameworks (e.g., Apache Spark, Kafka).
• Excellent problem-solving and analytical skills.
• Strong communication and interpersonal skills.
• Attention to detail and commitment to quality.
• In-depth understanding of data engineering principles, ETL processes, and database management.
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services.
• Knowledge of data governance, security, and regulatory standards.
• Ability to manage multiple tasks and prioritize effectively.
• Ability to work independently and as part of a team.

Experience : 4-6yrs

Job description :

We seek a talented Data Engineer with AI & ML knowledge to join our team. As a Data Engineer or MLOps Engineer, your primary responsibility will be to develop & integrate ML solutions that focus on technology improvements. Specifically, you will be working on projects involving leveraging AI/ML for Data Management Efficiencies & Query Optimizations.

Responsibilities:

1. Collaborate with cross-functional teams such as Data Scientists, Product Partners, and Partner Team Developers to identify opportunities for Big Data, Query (Spark, Hive SQL, BigQuery, SQL) tuning opportunities that can be solved using machine learning and generative AI.
2. Write clean, high-performance, high-quality, maintainable code.
3. Create backend applications using Python, Docker, Google Cloud & in-house ML frameworks to orchestrate end-to-end applications.
4. Design and develop Big Data Engineering Solutions & generative AI Applications ensuring scalability, efficiency, and maintainability of such solutions.
5. Implement prompt engineering techniques to fine-tune and enhance LLMs for better performance and application-specific needs.
6. Stay abreast of the latest advancements in the field of Generative AI Application Development and actively contribute to the research and development of new Generative AI Applications.

Requirements:

1. Proven experience working as a Big Data & MLOps Engineer, with a focus on Python, Google Cloud, Spark, Spark SQL, BigQuery, and Generative AI Applications.
2. Deep understanding and experience in tuning Dataproc, BigQuery, and Spark Applications.
3. Solid knowledge of software engineering best practices, including version control systems (e.g., Git), code reviews, and testing methodologies.

The Data Scientist focuses on developing algorithms, data analysis, and insights to drive business innovation and efficiency. This role involves working with large datasets, developing predictive models, and collaborating with cross-functional teams to deliver data-driven solutions.

1. Develop and implement data science projects, including the design and development of algorithms and models.
2. Collaborate with stakeholders to understand business requirements and translate them into data science solutions.
3. Analyze large datasets to extract insights, identify trends, and support decision-making.
4. Develop and validate predictive models, machine learning algorithms, and statistical analyses.
5. Ensure the accuracy, quality, and relevance of data science outputs.
6. Stay updated with the latest advancements in data science and machine learning, applying them to enhance solutions.
7. Provide support and guidance to other team members as needed.
8. Ensure compliance with data governance, security, and regulatory standards in all data science activities.
9. Prepare and present data science reports and documentation to senior management and stakeholders.
10. Participate in project planning and contribute to the development of project timelines and deliverables.
11. Perform other duties relevant to the job as assigned by the Sr. Data Scientist or senior management.

• Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field.
• Relevant certifications (e.g., Certified Data Scientist, Google Cloud Professional Data Engineer) are preferred.
• Minimum of 3 years of experience in data science or related fields.
• Experience in developing and implementing data science solutions for AI or technology-focused products.
• Strong programming skills in languages such as Python, R, or SQL.
• Proficiency in data science tools and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Excellent problem-solving and analytical skills.
• Strong communication and interpersonal skills.
• Attention to detail and commitment to quality.
• In-depth understanding of data science principles, machine learning algorithms, and statistical analysis.
• Familiarity with data visualization tools (e.g., Tableau, Power BI).
• Knowledge of data governance, security, and regulatory standards.
• Ability to manage multiple tasks and prioritize effectively.
• Strong attention to detail and commitment to delivering high-quality work.
• Ability to work independently and as part of a team.

SWATX is looking for a talented and driven Data Scientist to join our dynamic team. In this role, you will leverage your expertise in data analysis, machine learning, and statistical modeling to extract insights from complex datasets and drive data-driven decision making within the organization. You will work closely with business stakeholders to identify opportunities for leveraging data to improve products, services, and overall business performance.

Responsibilities:

• Analyze large datasets to identify trends, patterns, and insights that can inform business strategies.
• Develop and implement predictive models and machine learning algorithms to solve complex business problems.
• Collaborate with cross-functional teams to understand data requirements and provide analytical solutions that meet business needs.
• Design and conduct experiments to test hypotheses and validate results.
• Communicate findings and recommendations to stakeholders through presentations and reports.
• Continuously monitor and improve model performance through regular updates and refinements.
• Stay updated with the latest advancements in data science, machine learning, and AI technologies to apply best practices in your work.
• Build and maintain data pipelines to ensure the availability of data for analysis and reporting.
• Work with data engineering teams to ensure data is collected and stored effectively for analysis.

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Proven experience as a Data Scientist or in a similar analytical role.
• Strong programming skills in Python, R, or similar languages.
• Proficiency in SQL and experience with relational and non-relational databases.
• Experience with machine learning libraries and frameworks (e.g., Scikit-learn, TensorFlow, Keras).
• Knowledge of data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn) for communicating results.
• Understanding of statistical concepts and methodologies, and experience applying them to real-world scenarios.
• Excellent analytical and problem-solving skills.
• Strong communication skills, both verbal and written, in English and Arabic.

• Certified Data Scientist (CDS).
• Microsoft Certified: Azure Data Scientist Associate.
• Google Cloud Professional Data Engineer.
• SAS Certified Data Scientist.