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SAS Data Engineer

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  • Contact:

    Thomas Pluchot

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  • Published:

    25 Tage her

  • Duration:

    12 Months

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Job Description: Freelance Data Engineer

Location: Brussels, Hybrid

Languages Required: French or Dutch, and English

Contract Type: Freelance

About the Client: Our client is a dynamic and innovative organization seeking a highly skilled Data Engineer to join their team on a freelance basis. They are dedicated to leveraging data-driven insights to drive strategic decisions and enhance operational efficiency.

Job Summary: The client is looking for an experienced Data Engineer proficient in SAS Enterprise Guide (EG) and SAS Data Integration (DI) to support their data management and analytics initiatives. The ideal candidate will have a strong background in data engineering, excellent problem-solving skills, and the ability to communicate effectively in French or Dutch, as well as English.

Key Responsibilities:

  • Develop, maintain, and optimize data pipelines and ETL processes using SAS EG and SAS DI.
  • Collaborate with data analysts, data scientists, and other stakeholders to understand data requirements and deliver high-quality data solutions.
  • Perform data modeling, data integration, and data validation to ensure data accuracy and reliability.
  • Troubleshoot and resolve data-related issues promptly.
  • Document data engineering processes, workflows, and best practices.
  • Ensure compliance with data governance and security policies.

Required Skills and Qualifications:

  • Proficiency in SAS Enterprise Guide (EG) and SAS Data Integration (DI) is mandatory.
  • Strong knowledge of SQL and database management systems.
  • Experience with ETL tools and data warehousing concepts.
  • Familiarity with data modeling techniques and best practices.
  • Excellent problem-solving skills and attention to detail.
  • Ability to work independently and manage time effectively in a remote environment.
  • Strong communication skills in French or Dutch, and English.

Preferred Qualifications:

  • Experience in the finance, healthcare, or telecommunications industries.
  • Knowledge of additional data processing and analytics tools (e.g., Python, R).
  • Understanding of big data technologies and cloud platforms (e.g., AWS, Azure, Google Cloud).

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