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Senior Data Engineer

Senior Data Engineer

Datamatics Global Service
7-9 Years
Not Disclosed
Early Applicant
  • Posted a month ago
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Job Description

Please read the JD CarefullyJob Title: Senior Data Engineer / SSIS Engineer

Department/Section: Data and Analytics Office / Data Engineering

Language : Arabic & Non Arabic 

Location: Riyadh

Industry - Govt.Sector Org.

Experience: 7+ Years

Job Purpose

The Senior Data Engineer / SSIS Engineer is responsible for designing, building, and maintaining scalable data pipelines, ETL processes, and data marts that enable reliable analytics and data-driven decision-making. A key focus of this role is the development and maintenance of a robust semantic layer, ensuring structured, consistent, and business-friendly data access across the organization.

The role involves close collaboration with analytics, data science, and business teams to deliver high-quality data models, feature stores, and industrialized data products while upholding best practices in data engineering, data quality, and documentation.

Key Responsibilities1. Data Modeling
  • Design, develop, and maintain robust logical and physical data models that support analytical and reporting requirements.

  • Ensure models are scalable, performant, and aligned with business needs.

  • Apply industry-standard modeling techniques; experience with Data Vault methodology is a plus.

2. Semantic Layer Development
  • Design, implement, and maintain a centralized semantic layer to enable consistent and reusable business metrics.

  • Define and manage ontologies, taxonomies, hierarchies, and business definitions to ensure a common understanding of data across teams.

  • Enable self-service analytics by simplifying complex data structures for business users.

3. Data Pipeline Development (ETL/ELT)
  • Develop, optimize, and maintain ETL pipelines, with a strong focus on SSIS, to automate data ingestion, transformation, and loading.

  • Ensure high reliability, performance, and availability of data pipelines across multiple source systems and data platforms.

  • Support batch and near–real-time processing where required.

4. Data Quality & Consistency
  • Implement data quality checks and controls throughout the data lifecycle, starting from source systems.

  • Monitor data accuracy, completeness, and consistency, and proactively resolve data quality issues.

  • Collaborate with stakeholders to define and enforce data quality standards.

5. Collaboration with Stakeholders
  • Work closely with data scientists, analysts, BI developers, and business stakeholders to gather requirements and translate them into scalable data solutions.

  • Support analytical use cases, feature engineering, and reporting needs through well-designed data assets.

6. Documentation & Best Practices
  • Document data models, ETL workflows, semantic layer configurations, and data definitions.

  • Promote best practices in data engineering, naming conventions, version control, and deployment processes.

  • Ensure transparency, traceability, and knowledge sharing across teams.

7. Technical Mentorship
  • Mentor and guide junior data engineers.

  • Provide technical leadership in data modeling, SSIS development, and semantic layer design.

  • Contribute to continuous improvement of data engineering standards and frameworks.

Required Qualifications & Skills
  • Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.

  • Strong hands-on experience as a Senior Data Engineer or SSIS Engineer.

  • Advanced expertise in SSIS, SQL, and relational data warehouses.

  • Strong knowledge of data modeling techniques (star schema, snowflake, dimensional modeling).

  • Experience designing and maintaining data marts and semantic layers.

  • Solid understanding of data quality management and ETL best practices.

  • Strong communication skills and ability to work with both technical and non-technical stakeholders.

Nice to Have
  • Experience with Data Vault modeling.

  • Exposure to modern analytics platforms, cloud data services, or feature stores.

  • Experience supporting self-service BI and analytics use cases.

More Info

Job Type:
Industry:
Employment Type:

Key Skills

semantic layers

data modeling techniques

Data Vault modeling

data quality management

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