Data / AI Engineer Hybrid/Full remote

About the Opportunity

Our client, a key European organisation driving defence cooperation, innovation and capability development across Europe, is looking for a Data & AI Engineer to support the development of next-generation data, analytics and artificial intelligence capabilities.

This is an exciting opportunity to contribute to strategic initiatives involving data engineering, advanced analytics, AI-enabled solutions and secure information environments. You will work on innovative platforms designed to support data-driven decision-making while operating in a highly secure, international and technology-focused environment.

Role Overview

As a Data & AI Engineer, you will contribute to the design, development and deployment of core platform components, focusing on data engineering, analytics and AI-enabled capabilities.

The role requires strong expertise in working with both structured and unstructured data, enabling advanced reporting, analytics and AI-driven use cases within a secure and highly governed environment.

Key Responsibilities

Data Engineering & Integration

• Develop and maintain data pipelines integrating multiple heterogeneous data sources, including structured and unstructured information.
• Implement batch and near-real-time data ingestion processes.
• Perform data cleansing, validation and standardisation.
• 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 collaboration with Data Stewards and governance teams.
• Contribute to the creation of reusable datasets and data products from heterogeneous information sources.

Structured & Unstructured Data Management

• Design solutions combining 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.

Analytics & AI Enablement

• Implement analytics capabilities supporting operational and strategic decision-making.
• 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.

Automation & Orchestration

• 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.

Security & Compliance

• Implement security controls including identity and access management.
• Implement encryption for data at rest and in transit.
• Support audit logging requirements.
• Support the separation of classified and unclassified environments.
• Contribute to solutions deployable in secure or air-gapped environments.

Platform Development & Integration

• Build modular and scalable platform components using open standards and APIs.
• Contribute to integration with existing systems and external data sources.
• Support hybrid and sovereign deployment approaches.

Documentation & Knowledge Transfer

• Produce clear technical documentation.
• Support knowledge transfer activities with relevant stakeholders.

Profile Requirements

Mandatory Experience & Skills

Data Engineering & Architecture

• Proven experience designing and implementing ETL/ELT data pipelines.
• Strong knowledge of data lake and data warehouse architectures.
• Experience with modern data platforms such as Microsoft Fabric, Microsoft Copilot, Azure and open-source data platforms.

Structured & Unstructured Data

• Demonstrated experience handling and integrating structured data and unstructured data.
• Experience building end-to-end data pipelines across heterogeneous data sources.
• 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 and Machine Learning solutions, particularly involving text and document-based data.
• Understanding of explainability and traceability principles.

Engineering Practices

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

Nice-to-Have Skills

• Experience working in classified or restricted environments.
• Familiarity with Microsoft Purview or similar data 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 within public sector, defence or EU institutions.
• Experience with AI explainability or human-in-the-loop systems.

Skills & Competencies

• Hold, or be eligible to obtain, a national or EU Personnel Security Clearance at SECRET UE/EU SECRET level.
• Strong engineering mindset focused on scalable and modular solutions.
• Ability to operate in highly governed and security-sensitive environments.
• Pragmatic and structured approach focused on value, feasibility and incremental delivery.
• Ability to adapt to changing priorities.
• Ability to work across multiple technologies and evolving environments.
• Strong collaboration and communication skills.

? Please note: Only candidates who are nationals of one of the EU Member States are eligible to apply for this role.

Sounds exciting and want to know more?

Apply directly or contact Goffinet François.

• Proven experience designing and implementing ETL/ELT data pipelines.
• Strong knowledge of data lake and data warehouse architectures.
• Experience with modern data platforms such as Microsoft Fabric, Microsoft Copilot, Azure and open-source data platforms.

Structured & Unstructured Data

• Demonstrated experience handling and integrating structured data and unstructured data.
• Experience building end-to-end data pipelines across heterogeneous data sources.
• 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 and Machine Learning solutions, particularly involving text and document-based data.
• Understanding of explainability and traceability principles.

Engineering Practices

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

Nice-to-Have Skills

• Experience working in classified or restricted environments.
• Familiarity with Microsoft Purview or similar data 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 within public sector, defence or EU institutions.
• Experience with AI explainability or human-in-the-loop systems.

Skills & Competencies

• Hold, or be eligible to obtain, a national or EU Personnel Security Clearance at SECRET UE/EU SECRET level.
• Strong engineering mindset focused on scalable and modular solutions.
• Ability to operate in highly governed and security-sensitive environments.
• Pragmatic and structured approach focused on value, feasibility and incremental delivery.
• Ability to adapt to changing priorities.
• Ability to work across multiple technologies and evolving environments.
• Strong collaboration and communication skills.