وظيفة مهندس بيانات أول لدى Jobgether في السعودية
Data Engineer - Senior
🏢 Jobgether
تفاصيل الوظيفة
تمثل Jobgether شركة شريكة في هذا الإعلان عن وظيفة مهندس بيانات أول (Senior Data Engineer) للعمل عن بُعد في السعودية، ضمن مبادرة تحول رقمي كبيرة.
المهام والمسؤوليات
- تصميم وتطوير وصيانة حلول بيانات قابلة للتوسع وموثوقة تدعم برنامج تحول رقمي واسع النطاق.
- بناء وتحسين مسارات ETL/ELTP قوية تدمج البيانات من مصادر متنوعة في مجموعات بيانات موثوقة وجاهزة للتحليل.
- تطوير حلول بيانات سحابية باستخدام نظام Microsoft Azure البيئي، بما في ذلك Azure Data Factory وAzure Databricks وAzure Synapse Analytics وAzure Data Lake Storage Gen2 وAzure SQL والخدمات ذات الصلة.
- استخدام Python وSQL لتطوير تحويلات البيانات، وسير العمل، وعمليات التكامل، وحلول البيانات التحليلية.
- تصميم وإدارة نماذج وهياكل بيانات تدعم قابلية التوسع والموثوقية والأداء وجودة البيانات.
- العمل بشكل موسع مع Azure Databricks وDelta Lake لبناء وتحسين حلول معالجة وتخزين بيانات حديثة.
- التعاون مع أصحاب المصلحة من الأعمال، ومالكي المنتجات، ومهندسي البيانات، والفرق التقنية لفهم المتطلبات وترجمتها إلى حلول هندسة بيانات فعالة.
- تطبيق ممارسات التحكم في الإصدارات وأفضل الممارسات الهندسية باستخدام أدوات مثل Git لدعم التطوير التعاوني القابل للصيانة.
- الاستفادة من الأدوات المدعومة بالذكاء الاصطناعي عند الاقتضاء لتوليد الكود، تحليل البيانات، الأتمتة، التحسين، وغيرها من أنشطة هندسة البيانات.
- استكشاف المشكلات التقنية وإصلاحها، وتحسين سير عمل البيانات، وتحسين أداء المسارات وموثوقيتها وقابليتها للصيانة باستمرار.
- التواصل بوضوح حول المفاهيم التقنية والمساهمة في التعاون الفعّال عبر فرق الأعمال والتقنية.
الشروط والمتطلبات
- خبرة عملية لا تقل عن 5 سنوات في استخدام Python وSQL في بيئة هندسة البيانات.
- خبرة لا تقل عن 3 سنوات في العمل مع خدمات Azure، بما في ذلك Azure Storage وAzure SQL وAzure Synapse وAzure networking.
- خبرة عملية لا تقل عن 3 سنوات في Azure Databricks وDelta Lake.
- خبرة لا تقل عن 3 سنوات في تصميم حلول البيانات وتطوير مجموعات بيانات موثوقة وجاهزة للتحليل.
- خبرة لا تقل عن 4 سنوات في أنظمة التحكم في الإصدارات، وخاصة Git.
- خبرة عملية لا تقل عن سنة واحدة في استخدام أدوات الذكاء الاصطناعي لتوليد الكود، تحليل البيانات، الأتمتة، التحسين، أو المهام ذات الصلة بهندسة البيانات.
- فهم قوي لمبادئ هندسة البيانات، وعمليات ETL/ELTP، وتكامل البيانات، وتطوير مسارات البيانات.
- قدرات متقدمة في تطوير SQL وتحويل البيانات.
- خبرة مثبتة في العمل مع منصات البيانات السحابية وهياكل البيانات الحديثة.
- مهارات تحليلية وحل مشكلات قوية مع نهج منظم لتشخيص وحل التحديات التقنية المعقدة.
- مهارات تواصل وتعاون ممتازة، مع القدرة على العمل بفعالية مع الفرق التقنية وأصحاب المصلحة من الأعمال.
المزايا
- وظيفة عن بُعد بالكامل، مما يتيح مرونة العمل من سلوفينيا.
- فرصة للمساهمة في مبادرة تحول رقمي واسعة النطاق ذات نطاق كبير في هندسة البيانات.
- العمل مع نظام سحابي حديث من Microsoft Azure وتقنيات هندسة بيانات شائعة الاستخدام.
- التعرض لمنصات وأدوات متقدمة تشمل Azure Databricks وDelta Lake وAzure Synapse وAzure Data Factory وPython وSQL.
- فرصة لتطبيق أدوات هندسة مدعومة بالذكاء الاصطناعي لتحسين التطوير والأتمتة والتحليل والتحسين.
- التعاون مع فرق متعددة التخصصات تشمل أصحاب المصلحة من الأعمال ومالكي المنتجات ومهندسي البيانات والمتخصصين التقنيين.
- فرصة العمل على حلول بيانات قابلة للتطوير وموجهة للإنتاج ذات تأثير مباشر على الأعمال.
- بيئة عمل عن بُعد مصممة لدعم الاستقلالية والمرونة.
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 Data Engineer - Senior based in Saudi Arabia.
This is a remote opportunity for an experienced data engineer to play a key role in a large-scale digital transformation initiative. You will design, develop, and maintain scalable data solutions that support reliable, analytics-ready information across the organization. Working closely with business stakeholders, product owners, architects, and technical teams, you will help turn diverse data sources into trusted and usable datasets. The role has a strong focus on the Microsoft Azure data ecosystem and modern cloud-based data architectures. You will work extensively with Azure Data Factory, Databricks, Synapse Analytics, Data Lake Storage Gen2, Python, SQL, and Delta Lake. This is an environment where strong engineering practices, problem-solving, and data quality directly contribute to business and technology outcomes.
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.
This is a remote opportunity for an experienced data engineer to play a key role in a large-scale digital transformation initiative. You will design, develop, and maintain scalable data solutions that support reliable, analytics-ready information across the organization. Working closely with business stakeholders, product owners, architects, and technical teams, you will help turn diverse data sources into trusted and usable datasets. The role has a strong focus on the Microsoft Azure data ecosystem and modern cloud-based data architectures. You will work extensively with Azure Data Factory, Databricks, Synapse Analytics, Data Lake Storage Gen2, Python, SQL, and Delta Lake. This is an environment where strong engineering practices, problem-solving, and data quality directly contribute to business and technology outcomes.
Accountabilities
- Design, develop, and maintain scalable, reliable data solutions supporting a large-scale digital transformation program.
- Build and optimize robust ETL/ELT pipelines that integrate data from diverse sources into trusted, analytics-ready datasets.
- Develop cloud-based data solutions using the Microsoft Azure ecosystem, including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure SQL, and related services.
- Use Python and SQL to develop data transformations, processing workflows, integrations, and analytical data solutions.
- Design and manage data models and architectures that support scalability, reliability, performance, and data quality.
- Work extensively with Azure Databricks and Delta Lake to build and optimize modern data processing and storage solutions.
- Collaborate with business stakeholders, product owners, data architects, and technical teams to understand requirements and translate them into effective data engineering solutions.
- Apply version control and engineering best practices using tools such as Git to support maintainable, collaborative development.
- Leverage AI-powered tools where appropriate for code generation, data analysis, automation, optimization, and other data engineering activities.
- Troubleshoot technical issues, optimize data workflows, and continuously improve pipeline performance, reliability, and maintainability.
- Communicate technical concepts clearly and contribute to effective collaboration across business and technical teams.
- At least 5 years of hands-on experience with Python and SQL in a data engineering environment.
- At least 3 years of experience working with Azure services, including Azure Storage, Azure SQL, Azure Synapse, and Azure networking.
- At least 3 years of hands-on experience with Azure Databricks and Delta Lake.
- At least 3 years of experience designing data solutions and developing trusted, analytics-ready datasets.
- At least 4 years of experience with version control systems, particularly Git.
- At least 1 year of practical experience using AI tools for code generation, data analysis, automation, optimization, or related data engineering tasks.
- Strong understanding of data engineering principles, ETL/ELT processes, data integration, and data pipeline development.
- Advanced SQL development and data transformation capabilities.
- Proven experience working with cloud-based data platforms and modern data architectures.
- Strong analytical and problem-solving abilities, with a structured approach to diagnosing and resolving complex technical challenges.
- Excellent communication and collaboration skills, with the ability to work effectively with both technical teams and business stakeholders.
- Ability to work independently in a remote environment while maintaining strong ownership, organization, and delivery focus.
- Fully remote position, offering flexibility to work from Slovenia.
- Opportunity to contribute to a large-scale digital transformation initiative with significant data engineering scope.
- Work with a modern Microsoft Azure cloud data ecosystem and widely used data engineering technologies.
- Exposure to advanced platforms and tools including Azure Databricks, Delta Lake, Azure Synapse, Azure Data Factory, Python, and SQL.
- Opportunity to apply AI-powered engineering tools to improve development, automation, analysis, and optimization.
- Collaboration with multidisciplinary teams including business stakeholders, product owners, data architects, and technical specialists.
- Opportunity to work on scalable, production-focused data solutions with direct business impact.
- Remote working environment designed to support autonomy and flexibility.
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 13 أغسطس 2026
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