Expert AI & Data Strategy

The opportunity

At Vantage Towers, we’re on a mission to power Europe’s sustainable digital transformation. As a leading tower company, we’re ushering in an era of technology-driven advances to help connect people, businesses, and internet-enabled devices like never before. We combine the scale, stability and quality of our tower network with the agility, optimism and energy of a start-up.

As a young TowerCo, we have already achieved strong results with a continued focus on accelerating growth and a special emphasis put on sustainability. As part of our team, you’ll work in a dynamic and multicultural environment that embraces open communication, collaboration and teamwork.

The Expert AI & Data Strategy is responsible for designing, building, optimising, and supporting robust data pipelines and data solutions that power Vantage Towers’ modern cloud-based data and analytics landscape. The role focuses on hands-on data engineering delivery and ensures that data is provided in a scalable, reliable, maintainable, and production-ready manner fo reporting, analytics, and future AI-enabled use cases. The role acts as the bridge between architecture and analytical consumption by translating platform principles into robust engineering implementation and trusted, consumption-ready data solutions.

If you’re ready to take responsibility and shape the future of telco infrastructure with us, then let’s level up in your career and reach the top, together.

Your Responsibilities

• Design, build, test, deploy, and support scalable data pipelines across a modern cloud-based data platform, with strong emphasis on GCP-based engineering patterns and cost-efficient use of cloud services.

• Build and optimise data solutions around BigQuery as a core analytical data platform, including performant transformation logic, structured datasets, and reusable engineering components.

• Implement data ingestion, integration, and event-driven or streaming patterns using technologies such as Pub/Sub and, where relevant, Kafka-based integration concepts.

• Develop and maintain orchestration and automation workflows for reliable end-to-end data processing, ideally in cloud-native orchestration environments.

• Apply sound data modelling and storage design principles to ensure scalable, performant, and maintainable structures for analytical consumption.

• Collaborate closely with analytics and AI stakeholders on preparing fit-for-purpose analytical datasets and ensuring effective handover into Power BI data models, reporting layers or AI use case enablement.

• Engineer and continuously improve reusable transformation layers and curated datasets for reporting, analytics, and AI-ready data consumption.

• Ensure high engineering quality through structured testing, versioning, documentation, monitoring, release discipline, and production support.

• Establish and improve data quality, reliability, traceability, and observability across the engineered data landscape.

• Collaborate closely with the GCP Architect to translate target-state architecture into pragmatic and robust implementation while keeping clear ownership boundaries between architecture and engineering delivery.

• Contribute to the practical use of AI in engineering work, for example to accelerate development, testing, documentation, troubleshooting, and productivity, while ensuring controlled, responsible, and quality-focused usage.

• Guide internal and external delivery contributors on data engineering best practices and challenge low-quality technical implementations where needed.

Your Profile

Core competencies, knowledge and experience:

• Strong hands-on expertise in cloud-based data engineering, with particular strength in GCP-oriented engineering patterns and modern data processing design.

• Deep understanding of BigQuery-centric data engineering, including transformation design, performance optimisation, and scaling of analytical datasets.

• Experience with data integration and messaging patterns such as Pub/Sub and ideally exposure to Kafka-based event streaming concepts.

• Solid experience in ETL / ELT design, orchestration, automation, and maintainable transformation pipelines.

• Strong understanding of data modelling and how engineered datasets should be structured for efficient downstream analytical consumption, including collaboration with Power BI data models.

• Experience with data quality controls, monitoring, observability, and structured documentation across the data lifecycle.

• Sound understanding of engineering best practices such as modular design, maintainability, testing, CI/CD-oriented delivery, and production support.

• Ability to collaborate effectively with architects, analysts, business stakeholders, and external partners in distributed environments.

• Strong communication, problem-solving, ownership, and stakeholder collaboration skills.

• Pragmatic understanding of how AI-assisted engineering methods can improve delivery speed and quality without shifting the role into an AI architect or data scientist profile

• Foundational AI literacy (classic ML and GenAI) to know when to use it - and when not to.

• University degree in computer science, engineering, information systems, data, or a related field; equivalent practical experience is also acceptable.

• Strong professional experience in data engineering with a proven track record of building and operating scalable data pipelines in complex environments.

• Hands-on experience with cloud-based data platforms and modern data engineering concepts, ideally including Google Cloud Platform.

• Practical experience with BigQuery and strong understanding of cloud-native analytical data processing.

• Experience with orchestration, automation, and transformation pipeline design in modern ETL / ELT environments.

• Experience with data integration or messaging concepts, ideally including Pub/Sub and exposure to Kafka or similar event-streaming technologies.

• Advanced SQL skills and strong programming capability, ideally in Python or Java.

• Strong understanding of data modelling, performance optimisation, and maintainable engineering design, including collaboration with downstream Power BI data modelling needs.

• Experience working in agile delivery environments and distributed, multinational stakeholder setups.

• Fluent English (C1), written and spoken.

• Some exposure to AI/GenAI use cases.

What we offer

• A diverse, multicultural setup based on our values – Accountability, Respect, Teamwork, and Trust – and the unique opportunity to shape the organisation
• An attractive salary package
• Meal Allowance: Delivered on Pluxee card - €10.20/day
• Pension Plan
• Full Health Insurance: For employees and co-payment for family members
• Life Insurance
• 7 extra vacation days: 4 flexible, plus 3 fixed — 1 on Carnival, 1 on Christmas, and half a day on Easter and New Year's.
• Parking Slot

  Interested? Send us your CV with your desired salary. Depending on the role, we generally invite you to two rounds of interviews before you receive your offer.

Not the right match? We have plenty of other opportunities to choose from in this department here.

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