Make an impact by working for sectors where technology is the enabler, everything is ground-breaking and there’s a constant need to be innovative.

Create and enhance projects in Java, Python, Angular, PHP, .NET and so much more while diving in the world of Blockchain, Artificial Intelligence, Data Science, Security and Internet of Things.

Be part of the team that combines business knowledge, technological edge and a design experience. Our different backgrounds and know-how are key in developing solutions and experiences for digital clients.

Face challenges and learn other ways of thinking and seeing the world - there’s always room for your energy and creativity.

About the role

We are seeking a motivated and data-driven engineer who is eager to learn, grow, and contribute to the design, development, and evolution of a Network Digital Twin platform. This initiative aims to create a real-time, data-powered representation of our network and service topology, enabling predictive analytics, service assurance, automation, and smarter decision-making across network operations.

You’ll collaborate with network architects, data engineers, and automation teams to model multi-domain topologies, ingest and correlate operational data, and participate in projects that explore the use of graph technologies to represent complex network relationships.

As a part of your job, you will:

• Design and implement scalable data models and architectures to represent network and service topologies.
• Develop and maintain real-time and batch data ingestion pipelines from various network and operational systems.
• Collaborate on data integration and correlation across multiple sources (e.g., inventory, assurance, telemetry, orchestration).
• Support the creation of analytics, automation, and visualization solutions that leverage the Network Digital Twin.
• Participate in exploring and applying graph databases (e.g., AWS Neptune, Neo4j) for relationship-based modeling and analytics.
• Work with solution architects to ensure the digital twin supports automation, AI, and data-driven decision-making.
• Ensure data integrity, consistency, and security across platforms and integrations.
• Collaborate with AI/ML teams to feed data models into predictive use cases such as anomaly detection and capacity forecasting.

What are we looking for?

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Network Engineering, or a related field.
• Solid understanding of data modeling, ETL processes, and data pipeline development.
• Experience working with data integration frameworks (e.g., Kafka, NiFi, Apache Camel) and APIs.
• Proficiency in at least one programming language such as Python, Java, or Scala.
• Strong analytical mindset with a curiosity for learning new data technologies and approaches.
• Interest in graph databases and network modeling — prior experience is a plus but not required.
• Familiarity with network concepts (IP/MPLS, SDN, 5G, cloud-native, etc.) is an advantage.

Nice to have:

• Experience with graph technologies (Neo4j, AWS Neptune, or similar).
• Exposure to telecom or large-scale network environments.
• Familiarity with TM Forum Open APIs (e.g., TMF638, TMF640, TMF633).
• Experience with visualization tools (e.g., Neo4j Bloom, GraphXR, Gephi).
• Understanding of AI/ML applications for network data.
• Knowledge of cloud-native infrastructure and microservices (Kubernetes, Docker).
• Experience working in Agile/DevOps teams.

Personal traits

• Ability to adapt to different contexts, teams, and Clients;
• Teamwork skills but also a sense of autonomy;
• Motivation for international projects and ok if travel is included;
• Willingness to collaborate with other players;
• Strong communication skills.
  

At Celfocus, we are committed to cultivate a diverse and inclusive workplace. As an equal-opportunity employer, we welcome applicants of all backgrounds, gender identities, and abilities. We are dedicated to providing reasonable accommodations for candidates with specific needs. If you require any adjustments during the selection process, please inform our Talent Acquisition Team.

Come join the Team!