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Data & AI Engineer

COSMOTE GLOBAL SOLUTIONS NV
CompanyCOSMOTE GLOBAL SOLUTIONS NV
CategoryEngineering
LocationBrussels
RemoteOn-site (inferred)
EmploymentContract
LevelNot stated
SalaryNot stated by the employer
Posted28 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (workable)
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Description
COSMOTE Global Solutions NV is seeking a skilled Data & AI Engineer to join our dynamic ICT team. As part of the OTE Group of Companies, we specialize in delivering cutting-edge ICT solutions and services spanning Cloud Services, Data Centre operations, Networking, Cybersecurity, Business Intelligence, Big Data, and more. In this role, you will contribute to the design, development, and deployment of core platform components, with a focus on data engineering, analytics, and AI-enabled capabilities. You will work across structured and unstructured data to enable reporting, advanced analytics, and AI-driven use cases. Collaborating closely with architects, developers, project leaders, and stakeholders, you will help deliver scalable, high-performance data solutions that meet the evolving technological needs of our clients. Responsibilities: Develop and maintain data pipelines that integrate multiple heterogeneous data sources, including both structured and unstructured information. Implement data ingestion processes, including batch and near-real-time processing. Perform data cleansing, validation and standardization to ensure reliable and consistent datasets. Apply metadata tagging and support data lineage across relevant data flows. Contribute to the development and maintenance of the Data and Product Catalogue. Implement data quality checks, validation rules and monitoring mechanisms across data pipelines and analytical workflows. Support the identification and remediation of data quality issues in cooperation with Data Stewards and relevant governance teams. Contribute to the creation of reusable datasets and data products from heterogeneous information sources. Design solutions that combine structured data, such as databases and tabular datasets, with unstructured data, such as documents, reports and text. Transform unstructured information into formats suitable for analysis, reporting and AI enabled processing. Enable unified analytical workflows and reporting across mixed data types. Support AI-driven processing of document-centric data. Implement analytics capabilities that support operational and strategic decision-making workflows. Contribute to the design and implementation of AI-enabled use cases. Ensure AI outputs are explainable, traceable and supported by appropriate human-in the-loop controls. Automate data pipelines, reporting workflows and recurring analytical processes. Implement event-driven processing, alerts and triggers where relevant. Support monitoring, logging and operational observability of platform processes. Implement security controls aligned with EU requirements, including identity and access management, encryption of data at rest and in transit, and audit logging. Support the separation of classified and unclassified environments. Contribute to solutions that can be deployed in secure or air-gapped environments. Build modular and scalable platform components using open standards and APIs. Contribute to integration with existing EDA systems and external data sources. Support hybrid and sovereign deployment approaches. Produce clear technical documentation and support knowledge transfer to relevant stakeholders. Requirements Data Engineering & Architecture Proven experience in designing and implementing data pipelines, including ETL/ELT. Strong knowledge of data lake and data warehouse architectures. Experience with modern data platforms, such as Microsoft Fabric, Copilot, the Azure ecosystem, and open-source data platforms.   Handling Structured & Unstructured Data (Critical Requirement) Demonstrated experience in handling and integrating structured data, such as databases and tabular datasets, and unstructured data, such as documents, reports, PDFs, and text corpora. Ability to build pipelines enabling end-to-end exploitation of heterogeneous data. Experience preparing data for reporting and advanced ana
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