Principal Data Engineer - Doha, , Qatar
منذ يوم
وصف الوظيفة
<\/h3>
Job Summary<\/span>
<\/h3>
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.<\/span>
<\/p>
Responsibilities and Duties<\/span>
<\/h3>- Design, develop, and maintain data
pipelines, ETL processes, and database systems to support AI and data science
initiatives.<\/span><\/span>
<\/span><\/span><\/li> - Collaborate with data scientists, AI/ML
engineers, and other stakeholders to understand data requirements and ensure
data availability and quality.<\/span><\/span>
<\/span><\/span><\/li> - Implement data governance, security, and
regulatory standards in all data engineering activities.<\/span><\/span>
<\/span><\/span><\/li> - Optimize data pipelines and processes for
scalability, performance, and cost -efficiency.<\/span><\/span>
<\/span><\/span><\/li> - Monitor and ensure the performance and
reliability of data systems, identifying and resolving issues as needed.<\/span><\/span>
<\/span><\/span><\/li> - Stay updated with the latest advancements
in data engineering technologies and best practices.<\/span><\/span>
<\/span><\/span><\/li> - Mentor and provide guidance to junior data
engineers and other team members.<\/span><\/span>
<\/span><\/span><\/li> - Prepare and present data engineering
reports and documentation to senior management and stakeholders.<\/span><\/span>
<\/span><\/span><\/li> - Participate in project planning and
contribute to the development of project timelines and deliverables.<\/span><\/span>
<\/span><\/span><\/li> - Perform other duties relevant to the job as
assigned by the Head of Data & AI Engineering or senior management.<\/span><\/span>
<\/span><\/li><\/ul><\/span>
<\/h3>
<\/div><\/span>
Requirements<\/h3>
<\/span><\/span><\/div>- Bachelor's degree in Data Engineering,
Computer Science, or a related field<\/span><\/span>
<\/span><\/span><\/li> - Relevant certifications (e.g., Google Cloud
Professional Data Engineer, AWS Certified Big Data – Specialty) are preferred<\/span><\/span>
<\/span><\/span><\/li> - Minimum of 8 years of experience in data
engineering or related fields<\/span><\/span>
<\/span><\/span><\/li> - Experience in designing and implementing
data pipelines, ETL processes, and database systems for AI or
technology -focused products<\/span><\/span>
<\/span><\/span><\/li> - Strong programming skills in languages such
as Python, SQL<\/span><\/span>
<\/span><\/span><\/li> - Proficiency in data engineering tools and
frameworks (e.g., Apache Spark, Kafka)<\/span><\/span>
<\/span><\/span><\/li> - Excellent problem -solving and analytical
skills<\/span><\/span>
<\/span><\/span><\/li> - Strong communication and interpersonal
skills<\/span><\/span>
<\/span><\/span><\/li> - Attention to detail and commitment to
quality<\/span><\/span>
<\/span><\/span><\/li> - In -depth understanding of data engineering
principles, ETL processes, and database management<\/span><\/span>
<\/span><\/span><\/li> - Familiarity with cloud platforms (e.g.,
AWS, Azure, Google Cloud) and their data services<\/span><\/span>
<\/span><\/span><\/li> - Knowledge of data governance, security, and
regulatory standards<\/span><\/span>
<\/span><\/span><\/li> - Ability to manage multiple tasks and
prioritize effectively<\/span><\/span>
<\/span><\/span><\/li> - Strong attention to detail and commitment
to delivering high -quality work<\/span><\/span>
<\/span><\/span><\/li> - Ability to work independently and as part
of a team<\/span><\/span>
<\/span><\/span><\/li> - Programming languages (e.g., Python)<\/span><\/span>
<\/span><\/span><\/li> - Data engineering tools and frameworks
(e.g., Apache Spark, Kafka)<\/span><\/span>
<\/span><\/span><\/li> - Cloud platforms (e.g., AWS, Azure, Google
Cloud)<\/span><\/span>
<\/span><\/span><\/li> - Data management systems (e.g., SQL, NoSQL
databases)<\/span><\/span>
<\/span><\/span><\/li> - Collaboration and communication tools
(e.g., Slack, Microsoft Teams)<\/span><\/span>
<\/span><\/span><\/li><\/ul>
<\/div><\/span>
pipelines, ETL processes, and database systems to support AI and data science
initiatives.<\/span><\/span>
<\/span><\/span><\/li>
engineers, and other stakeholders to understand data requirements and ensure
data availability and quality.<\/span><\/span>
<\/span><\/span><\/li>
regulatory standards in all data engineering activities.<\/span><\/span>
<\/span><\/span><\/li>
scalability, performance, and cost -efficiency.<\/span><\/span>
<\/span><\/span><\/li>
reliability of data systems, identifying and resolving issues as needed.<\/span><\/span>
<\/span><\/span><\/li>
in data engineering technologies and best practices.<\/span><\/span>
<\/span><\/span><\/li>
engineers and other team members.<\/span><\/span>
<\/span><\/span><\/li>
reports and documentation to senior management and stakeholders.<\/span><\/span>
<\/span><\/span><\/li>
contribute to the development of project timelines and deliverables.<\/span><\/span>
<\/span><\/span><\/li>
assigned by the Head of Data & AI Engineering or senior management.<\/span><\/span>
<\/span><\/li><\/ul>
<\/span>
<\/h3>
<\/div><\/span>
Requirements<\/h3>
<\/span><\/span><\/div>- Bachelor's degree in Data Engineering,
Computer Science, or a related field<\/span><\/span>
<\/span><\/span><\/li> - Relevant certifications (e.g., Google Cloud
Professional Data Engineer, AWS Certified Big Data – Specialty) are preferred<\/span><\/span>
<\/span><\/span><\/li> - Minimum of 8 years of experience in data
engineering or related fields<\/span><\/span>
<\/span><\/span><\/li> - Experience in designing and implementing
data pipelines, ETL processes, and database systems for AI or
technology -focused products<\/span><\/span>
<\/span><\/span><\/li> - Strong programming skills in languages such
as Python, SQL<\/span><\/span>
<\/span><\/span><\/li> - Proficiency in data engineering tools and
frameworks (e.g., Apache Spark, Kafka)<\/span><\/span>
<\/span><\/span><\/li> - Excellent problem -solving and analytical
skills<\/span><\/span>
<\/span><\/span><\/li> - Strong communication and interpersonal
skills<\/span><\/span>
<\/span><\/span><\/li> - Attention to detail and commitment to
quality<\/span><\/span>
<\/span><\/span><\/li> - In -depth understanding of data engineering
principles, ETL processes, and database management<\/span><\/span>
<\/span><\/span><\/li> - Familiarity with cloud platforms (e.g.,
AWS, Azure, Google Cloud) and their data services<\/span><\/span>
<\/span><\/span><\/li> - Knowledge of data governance, security, and
regulatory standards<\/span><\/span>
<\/span><\/span><\/li> - Ability to manage multiple tasks and
prioritize effectively<\/span><\/span>
<\/span><\/span><\/li> - Strong attention to detail and commitment
to delivering high -quality work<\/span><\/span>
<\/span><\/span><\/li> - Ability to work independently and as part
of a team<\/span><\/span>
<\/span><\/span><\/li> - Programming languages (e.g., Python)<\/span><\/span>
<\/span><\/span><\/li> - Data engineering tools and frameworks
(e.g., Apache Spark, Kafka)<\/span><\/span>
<\/span><\/span><\/li> - Cloud platforms (e.g., AWS, Azure, Google
Cloud)<\/span><\/span>
<\/span><\/span><\/li> - Data management systems (e.g., SQL, NoSQL
databases)<\/span><\/span>
<\/span><\/span><\/li> - Collaboration and communication tools
(e.g., Slack, Microsoft Teams)<\/span><\/span>
<\/span><\/span><\/li><\/ul>
<\/div><\/span>
Computer Science, or a related field<\/span><\/span>
<\/span><\/span><\/li>
Professional Data Engineer, AWS Certified Big Data – Specialty) are preferred<\/span><\/span>
<\/span><\/span><\/li>
engineering or related fields<\/span><\/span>
<\/span><\/span><\/li>
data pipelines, ETL processes, and database systems for AI or
technology -focused products<\/span><\/span>
<\/span><\/span><\/li>
as Python, SQL<\/span><\/span>
<\/span><\/span><\/li>
frameworks (e.g., Apache Spark, Kafka)<\/span><\/span>
<\/span><\/span><\/li>
skills<\/span><\/span>
<\/span><\/span><\/li>
skills<\/span><\/span>
<\/span><\/span><\/li>
quality<\/span><\/span>
<\/span><\/span><\/li>
principles, ETL processes, and database management<\/span><\/span>
<\/span><\/span><\/li>
AWS, Azure, Google Cloud) and their data services<\/span><\/span>
<\/span><\/span><\/li>
regulatory standards<\/span><\/span>
<\/span><\/span><\/li>
prioritize effectively<\/span><\/span>
<\/span><\/span><\/li>
to delivering high -quality work<\/span><\/span>
<\/span><\/span><\/li>
of a team<\/span><\/span>
<\/span><\/span><\/li>
<\/span><\/span><\/li>
(e.g., Apache Spark, Kafka)<\/span><\/span>
<\/span><\/span><\/li>
Cloud)<\/span><\/span>
<\/span><\/span><\/li>
databases)<\/span><\/span>
<\/span><\/span><\/li>
(e.g., Slack, Microsoft Teams)<\/span><\/span>
<\/span><\/span><\/li><\/ul>
<\/div><\/span>
وظائف مماثلة
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