وظيفة مهندس بيانات أول (Python / AWS / ML Pipelines) شاغرة لدى Jobgether في السعودية
Senior Data Engineer (Python / AWS / ML Pipelines)
تفاصيل الوظيفة
تُعلن Jobgether، بالنيابة عن شركة شريكة، عن توفر وظيفة Senior Data Engineer (Python / AWS / ML Pipelines) في السعودية. ستعمل على بناء وتشغيل خطوط أنابيب بيانات وتعلّم آلة واسعة النطاق في بيئة إنتاج، بالتعاون مع علماء البيانات ومهندسي التعلّم الآلي.
المهام والمسؤوليات
- بناء وصيانة وتحسين خطوط أنابيب بيانات وتعلّم آلة إنتاجية تدعم التنبؤ واتخاذ القرارات المستندة إلى البيانات.
- تطوير مهام ETL وسير عمل معالجة البيانات باستخدام Python، مع ضمان قابلية التوسع والموثوقية والصيانة.
- تصميم وتنسيق سير العمل باستخدام تقنيات مثل Apache Airflow و AWS Step Functions.
- استخدام AWS Glue لمعالجة البيانات وتحويلها وتنفيذ خطوط الأنابيب.
- دعم نشر وتشغيل نماذج التعلّم الآلي باستخدام AWS SageMaker.
- العمل عن كثب مع علماء البيانات ومهندسي التعلّم الآلي لنقل النماذج والحلول التحليلية بشكل موثوق إلى الإنتاج.
- مراقبة صحة وأداء خطوط الأنابيب، واستكشاف المشكلات الإنتاجية وإصلاحها، وتنفيذ تحسينات في الموثوقية وقابلية التوسع والكفاءة.
- المساهمة في القرارات المعمارية والتقنية المتعلقة بمنصة البيانات والبنية التحتية للتعلّم الآلي وسير العمل الإنتاجي.
- التعاون بفاعلية مع فرق Agile موزعة ومتعددة الوظائف، والمساهمة بأفكار تحسّن الممارسات الهندسية والتسليم.
الشروط والمتطلبات
- خبرة مهنية قوية في Python وتطبيقه في هندسة البيانات والأنظمة الإنتاجية.
- خبرة مثبتة في بناء وصيانة خطوط أنابيب البيانات و/أو خطوط أنابيب التعلّم الآلي في الإنتاج.
- خبرة عملية في Apache Airflow لتنسيق سير العمل.
- خبرة عملية في AWS Step Functions و AWS Glue.
- خبرة في نشر ودعم نماذج التعلّم الآلي باستخدام AWS SageMaker.
- خبرة عملية قوية في خدمات AWS السحابية وبيئات الإنتاج السحابية.
- خبرة في العمل مع أنظمة تعمل على نطاق واسع، مع فهم قوي لاعتبارات الموثوقية والأداء.
- خبرة في التعاون الوثيق مع علماء البيانات ومهندسي التعلّم الآلي وأصحاب المصلحة التقنيين الآخرين.
- مهارات قوية في استكشاف الأخطاء وإصلاحها والتحليل وحل المشكلات.
- مهارات ممتازة في التواصل باللغة الإنجليزية كتابةً وتحدثًا.
- القدرة على العمل بشكل مستقل وتعاوني ضمن فرق موزعة ومتعددة الوظائف.
- خبرة في GCP تُعد ميزة إضافية (غير مطلوبة).
- الإلمام بأدوات المراقبة والملاحظة يُعد ميزة إضافية.
المزايا
- بيئة عمل تعاونية تُشارك فيها المسؤولية واتخاذ القرارات عبر الفريق.
- ثقافة Agile تشجع الموظفين على المساهمة بأفكارهم والتأثير في الاتجاه التقني.
- نهج داعم للتعلّم من الأخطاء والتحسين المستمر لأساليب العمل.
- فرص للعمل على مشاريع مختلفة وتوسيع الخبرات التقنية.
- تدريب مستمر وإرشاد وتطوير مهني.
- فرص للنمو الوظيفي والتعرض لتقنيات وتحديات جديدة.
- إمكانية السفر بغرض العمل.
- ترتيبات عمل مرنة تناسب الفريق الموزع.
- قد يختلف الراتب الإضافي والرعاية الصحية ومزايا التوظيف الأخرى وفقًا للشروط المحلية في سلوفينيا.
عرض النص الأصلي للإعلان
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer (Python / AWS / ML Pipelines) based in Saudi Arabia.
As a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines in a production environment.
You will work across data engineering, cloud infrastructure, and machine learning operations to turn models into reliable production workflows.
The role focuses heavily on Python, AWS, ETL, workflow orchestration, and scalable ML infrastructure.
You will collaborate closely with Data Scientists and ML Engineers to productionize forecasting and data-driven solutions.
You will also help improve the reliability, performance, and observability of critical data pipelines.
Working within distributed Agile teams, you will contribute to architecture decisions and technical improvements across the data platform.
This is an opportunity to work on challenging production systems while continuing to develop your cloud and ML engineering expertise.
Accountabilities
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
As a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines in a production environment.
You will work across data engineering, cloud infrastructure, and machine learning operations to turn models into reliable production workflows.
The role focuses heavily on Python, AWS, ETL, workflow orchestration, and scalable ML infrastructure.
You will collaborate closely with Data Scientists and ML Engineers to productionize forecasting and data-driven solutions.
You will also help improve the reliability, performance, and observability of critical data pipelines.
Working within distributed Agile teams, you will contribute to architecture decisions and technical improvements across the data platform.
This is an opportunity to work on challenging production systems while continuing to develop your cloud and ML engineering expertise.
Accountabilities
- Build, maintain, and improve production-grade data and machine learning pipelines supporting forecasting and data-driven decision-making.
- Develop ETL and data-processing workflows using Python, ensuring they are scalable, reliable, and maintainable.
- Design and orchestrate workflows using technologies such as Apache Airflow and AWS Step Functions.
- Use AWS Glue for data processing, transformation, and pipeline execution.
- Support the deployment and operationalization of machine learning models using AWS SageMaker.
- Work closely with Data Scientists and ML Engineers to move models and analytical solutions reliably into production.
- Monitor pipeline health and performance, troubleshoot production issues, and implement improvements to reliability, scalability, and efficiency.
- Contribute to architectural and technical decisions related to the data platform, ML infrastructure, and production workflows.
- Collaborate effectively with distributed, cross-functional Agile teams and contribute ideas that improve engineering practices and delivery.
- Strong professional experience with Python and its application to data engineering and production systems.
- Proven experience building and maintaining data pipelines and/or machine learning pipelines in production.
- Hands-on experience with Apache Airflow for workflow orchestration.
- Practical experience with AWS Step Functions and AWS Glue.
- Experience deploying and supporting machine learning models using AWS SageMaker.
- Strong hands-on experience with AWS cloud services and cloud-based production environments.
- Experience working with systems operating at significant scale, with a strong understanding of reliability and performance considerations.
- Experience collaborating closely with Data Scientists, ML Engineers, and other technical stakeholders.
- Strong troubleshooting, analytical, and problem-solving abilities.
- Excellent written and verbal English communication skills.
- Comfortable working independently and collaboratively within distributed, cross-functional teams.
- Experience with GCP is a plus but not required.
- Familiarity with monitoring and observability tools is also advantageous.
- Collegial working environment where responsibility and decision-making are shared across the team.
- Agile culture where employees are encouraged to contribute ideas and influence technical direction.
- Supportive approach to learning from mistakes and continuously improving ways of working.
- Opportunities to work on different projects and broaden your technical experience.
- Ongoing training, mentoring, and professional development.
- Opportunities for career growth and exposure to new technologies and challenges.
- Possibility of business travel.
- Flexible working arrangements appropriate to a distributed team.
- Additional salary, healthcare, and other employment benefits may vary according to local terms in Slovenia.
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
المصدر: LinkedIn - أُضيفت للموقع في 1 أكتوبر 2026
رقم الإعلان لدى المصدر: 4472564142
رقم الإعلان لدى المصدر: 4472564142