Data & AI Engineer

Cosmote Global Solutions; Brussel; Sur place; EUR 70 000 - 100 000; Plein temps

Résumé du poste

Cosmote Global Solutions NV is seeking a skilled Data & AI Engineer to join our ICT team in Belgium. You will design, build, and deploy core data platform components to enable analytics, reporting, and AI use cases across structured and unstructured data.

You will collaborate with architects, developers, and stakeholders to deliver scalable data solutions, ensure data quality, and contribute to data governance, catalogues, and secure deployments in hybrid and sovereign environments.

Qualifications

• Proven experience designing and implementing data pipelines (ETL/ELT).
• Strong knowledge of data lake and data warehouse architectures.
• Experience with modern data platforms (Microsoft Fabric, Azure, open source).
• Handling structured and unstructured data in pipelines for analytics and reporting.
• Exposure to AI/ML solutions on text/document data.
• Familiarity with data governance and data catalogues.

Responsabilités

• Develop and maintain data pipelines integrating heterogeneous sources.
• Implement batch and near-real-time data ingestion and processing.
• Ensure data cleansing, validation, and standardization for reliable datasets.
• Contribute to Data and Product Catalogue development and maintenance.
• Apply data quality checks and monitoring across pipelines and analytics.
• Support AI-enabled use cases and document-centric data processing.
• Ensure AI outputs are explainable and auditable with human-in-the-loop controls.
• Produce technical documentation and support knowledge transfer.

Connaissances

Data pipelines

ETL/ELT

Data governance

AI/ML exposure

DevOps

Git

CI/CD

Data modelling

Explainability

Outils

Microsoft Fabric

Copilot

Azure

Purview

MCP servers

Data catalogs

Description du poste

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 analytics
• Ability to structure unstructured information using metadata, classification, and transformation techniques

Analytics & AI

• Experience with analytics development and data modelling
• Exposure to AI/ML solutions, particularly on text- or document-based data
• Understanding of explainability and traceability principles

Engineering Practices

• Knowledge of DevOps, Git, CI/CD, and pipeline automation
• Ability to deliver in multi-stakeholder environments

Additional Desirable Skills

• Experience with classified or restricted environments, such as EUCI or equivalent.
• Familiarity with Microsoft Purview or similar governance tools.
• Ability to create and work with MCP servers.
• Experience with data catalogues and business glossaries.
• Experience with cross-domain data handling.
• Experience with hybrid or sovereign cloud environments.
• Experience in public sector, defence or EU institutions.
• Experience in AI explainability or human-in-the-loop systems

Profile & Mindset

• Hold, or be in a position to obtain, a valid Personnel Security Clearance Certificate, national or EU PSC at SECRET UE/EU SECRET level.
• Strong engineering mindset, with a focus on scalable and modular solutions.
• A pragmatic and structured approach, focused on value, feasibility and incremental delivery.
• Ability to operate in highly governed and security-sensitive environments.
• Pragmatic and structured approach to delivery, focused on value and feasibility.
• Ability to adapt to changing priorities.
• Ability to adapt to different technologies.
• Strong collaboration and communication skills