Data Engineer - Deadline 27/05/25

Following tasks will be performed by external service provider:

•          Data Infrastructure Design and Implementation: supervise the development and implementation of robust data storage and pipelines to support complex data challenges, ensuring systems are scalable, efficient, and aligned with project objectives.

•          Information Modeling and Data Flow Definition: Define and oversee the creation of data models and flows, working closely with stakeholders to ensure optimal performance and minimal impact.

•          Data Transformation Supervision: Specify and supervise data transformations necessary for processing and analysis, ensuring data quality and consistency.

•          Stakeholder Collaboration: Engage with stakeholders (Member States and trade partners) to identify data needs and implement solutions that support business objectives and regulatory requirements.

•          Data Security and Compliance: Ensure adherence to data security policies, focusing on integrity, confidentiality, and personal data privacy by design, in all data processes.

•          Analytics and AI Support: Collaborate with data scientists to design infrastructure supporting machine learning, statistical modeling, and data visualization projects.

•          Continuous Optimization: Monitor and optimize data systems performance, ensuring high reliability and efficiency.

•          Data Governance: contribute to data governance and policy definition supervision and enforcement, ensuring transparency and accountability in all data management activities.

Following skills and knowledge are required for the performance of the above listed tasks: 

•          Strong foundation in data engineering and best practices for data modeling and pipeline development.

•          Proficiency in programming languages such as Python, SQL, and data processing frameworks like Apache Spark or Kafka.

•          Experience with cloud platforms like OVH, AWS or AZURE for deploying and managing data infrastructure.

•          Commitment to data security principles and experience implementing secure data systems.

•          Ability to collaborate effectively with cross-functional teams and communicate complex technical concepts to both technical and non-technical stakeholders.

•          Experience in supporting data science projects through efficient data handling and processing.

•          Knowledge of data governance principles. 

Following specific expertise is mandatory for the performance of tasks:

•          A minimum of 5-7 years of experience in data engineering roles, with a focus on cloud-based environments and high-security requirements.

•          Relevant certifications such as Certified Data Scientist, AWS Certified Data Analytics, or Azure Data Engineer Associate are highly desirable.

•          Demonstrated experience in managing data projects that require high agility, innovation, and adaptability to change.

Level : 8 to 10

Delivery mode: Near Site (Brussels)