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    Data Engineer - Riyadh, المملكة العربية السعودية - Talent Pal

    Talent Pal
    Talent Pal Riyadh, المملكة العربية السعودية

    منذ يومين

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    وصف

    Data Engineer

    As a Data Engineer at NEOM EC12 you will play a pivotal role in shaping and implementing our data strategy. This strategic position is crucial for transforming raw data into meaningful insights contributing to informed decisionmaking across various stakeholders. If you are passionate about leveraging data to drive positive educational outcomes this role offers a unique opportunity to lead the development of a robust data infrastructure.

    • Data Strategy Development:
      • Collaborate with stakeholders to assess existing data infrastructure and contribute to the development of a comprehensive data strategy aligned with organizational objectives.
      • Create a roadmap for implementing the data strategy outlining key milestones and timelines for achieving strategic goals.
      • Explore emerging technologies and trends in data engineering to propose innovative solutions that enhance the organizations data capabilities.
      • Anticipate future data needs and design scalable data solutions to adapt to evolving organizational requirements.
      • Ensure alignment of the data strategy with broader business goals and objectives.
    • Dashboard Creation:
      • Work closely with stakeholders to understand reporting and visualization requirements.
      • Design and implement data models supporting the creation of interactive and insightful dashboards.
      • Utilize visualization tools like Tableau Power BI or equivalent for creating visually appealing and userfriendly dashboards.
      • Optimize queries and data retrieval processes to ensure realtime or nearrealtime insights.
      • Provide training and documentation to endusers on effective usage and interpretation of dashboard information.
    • Data Integration and Management:
      • Design implement and maintain Extract Transform Load (ETL) processes for efficient data integration from various sources.
      • Implement data quality processes to ensure accuracy and reliability of integrated data.
      • Develop strategies for managing master data to ensure consistency across the organization.
      • Implement solutions for realtime data processing and streaming as required by the business.
      • Conduct rigorous testing of integrated data to identify and resolve any issues related to data integrity.
    • Database Architecture:
      • Design and implement database structures aligned with performance scalability and business requirements.
      • Implement effective indexing strategies to optimize database query performance.
      • Apply normalization and denormalization techniques based on the specific needs of the data.
      • Develop and implement robust backup and recovery plans to safeguard data against loss or .
      • Implement security measures to protect sensitive data including access controls encryption and auditing.
    • Collaboration with stakeholders:
      • Collaborate with stakeholders to understand their data requirements for analytical purposes.
      • Assist stakeholders in exploring and understanding available data sources ensuring access to relevant information.
      • Work closely with stakeholders to optimize SQL queries and provide guidance on efficient data retrieval techniques.
      • Collaborate in interpreting data results providing insights and helping stakeholders derive meaningful conclusions.
      • Establish a continuous feedback loop with stakeholders to refine and enhance data solutions based on evolving needs.
    • Data Governance and Quality:
      • Contribute to the development and enforcement of data governance policies and standards.
      • Establish processes and tools for ongoing monitoring of data quality initiating corrective actions when necessary.
      • Ensure data practices adhere to regulatory requirements and industry standards related to data governance.
      • Conduct training sessions and communicate data governance principles to stakeholders to foster a culture of data quality and compliance.
    • CloudBased Solutions:
      • Design and implement data solutions leveraging cloud platforms such as AWS Azure or Google Cloud.
      • Utilize cloud scalability features to accommodate growing data volumes and processing demands.
      • Implement costeffective solutions in the cloud by optimizing resource utilization and leveraging serverless or managed services.
      • Implement robust security measures in the cloud including encryption access controls and monitoring.
    • Training and Documentation:
      • Provide training to endusers on data tools dashboards and reporting systems.
      • Create and maintain comprehensive documentation for data engineering processes.
    • Security and Compliance:
      • Implement robust security measures to protect sensitive data.
      • Ensure compliance with data privacy regulations and standards.

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