Semantic Data Engineer

Hi there! 

We are Capgemini Engineering. A brand part of the Capgemini Group.

We have the mission to empower every person and every organization on the planet to achieve more. Our culture is centered on embracing a growth mindset, diversity, inclusion, a purpose of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. You can learn more about Capgemini Engineering here: https://www.youtube.com/watch?v=MZ0Z6PjdnQo

 

You can help us to achieve our mission!

Now, we are part of Capgemini Group and we have more than 300,000 team members in nearly 50 countries, and we work with sectors such as aeronautics, automotive, communications, energy, life sciences, software & internet, space & defense and consumer products.

Your Mission 

Capgemini Engineering is constantly growing and attentive to market opportunities and in search of the best professionals to join its team. We are looking for a Semantic Data Engineer, so if you are looking for a new challenge and with great prospects for growth in your career, come join us.

 

Your role :

You will work for one of the largest pharmaceutical companies in the world, consistently ranked in the global top five.

The semantic Data Engineer will play a crucial role in designing, developing and implementing data solutions that leverage semantic technologies to enhance data understanding and integration. Main responsibilities:

 

• To bridge gap between structured and unstructured data applying semantic modelling and ontologies.
• Data Integration: Integrate and consolidate data from various sources, ensuring that it is structured and tagged in a way that preserves its semantic meaning.
• Ontology Development: Create and maintain ontologies, which are formal representations of knowledge that define concepts, relationships, and properties in a specific domain.
• Data Modeling: Design and implement data models that capture the semantic relationships and attributes of the data. This might involve using graph databases, RDF stores, or other semantic data stores.
• Linked Data: Work with linked data principles to enable interoperability and integration of data across different systems and domains.
• Semantic Web Standards: Stay up-to-date with standards and technologies related to the Semantic Web, such as RDF, SPARQL, and other W3C recommendations.
• Natural Language Processing (NLP): Leverage NLP techniques to extract and process unstructured text data, enhancing the understanding of the semantic context.
• Data Quality Assurance: Implement processes to ensure data quality, accuracy, and consistency, which is especially crucial when dealing with semantic data.

 

Your profile :

 

• Semantic Technologies: Proficiency in RDF, OWL, RDFS, and other Semantic Web technologies.
• Data Engineering: Strong foundation in traditional data engineering concepts, including ETL processes, data warehousing, and database management.
• Programming Languages: Knowledge of languages like Python, Java, or JavaScript is often beneficial, especially when working with APIs and implementing custom solutions.
• Linked Data Principles: Familiarity with principles and standards for publishing and consuming linked data on the web.
• Ontology Design and Development: Ability to create and manage ontologies that accurately represent the knowledge in a specific domain.
• NLP: Basic understanding of NLP techniques for processing and extracting meaning from text data.
• Data Governance and Compliance: Knowledge of data governance principles and compliance requirements, especially in industries with strict regulatory standards.

Our offer:

• Integration in a multicultural and inclusive team environment;
• Possibility to participate in international projects;
• Annual Individual Training Plan;
• Continuous training on Next;
• Referral bonuses for recommending your friends to Capgemini Engineering;
• Offices in great locations;
• Career evolution.