At a Glance
- Tasks: Design and develop innovative data architectures to transform enterprise data into insights.
- Company: Join a forward-thinking consultancy dedicated to inclusivity and innovation.
- Benefits: Competitive pay, fully remote work, and opportunities for professional growth.
- Other info: Collaborate with talented professionals and shape the future of data engineering.
- Why this job: Be at the forefront of data innovation and make a real impact in the energy sector.
- Qualifications: 7-12 years in graph databases and semantic modelling; strong query language skills required.
The predicted salary is between 60000 - 80000 £ per year.
Adecco is an employment consultancy. We put expertise, energy, and enthusiasm into improving everyone's chance of being part of the workplace. We respect and appreciate people of all ethnicities, generations, religious beliefs, sexual orientations, gender identities, and more. We do this by showcasing their talents, skills, and unique experience in an inclusive environment that helps them thrive.
Are you passionate about transforming enterprise data into meaningful insights? Do you thrive in innovative environments where you can shape the future of data architecture? If so, our client is looking for you! Join us as a Semantic Graph & Ontology Architect and play a pivotal role in developing a Smart Data Fabric that unifies various data sources like Snowflake, SharePoint, and ERP systems, all while enhancing AI capabilities through a sophisticated semantic, graph-native foundation.
Duration: 6 Months (extension options)
Location: Fully Remote
Rate: £ Competitive (outside ir35)
How You'll Make an Impact:
- Graph & Semantic Architecture: Design scalable graph schemas (LPG and/or RDF/OWL) to meet semantic and inference requirements. Author and optimise queries using Cypher, Gremlin, and SPARQL for seamless data traversal and reasoning. Define canonical entity models and mapping layers to integrate diverse data sources.
- Ontology Engineering & Reasoning: Create and maintain formal ontologies and taxonomies while governing their versioning and lifecycle. Implement logical inference for agent decision-making and ensure workflow integrity. Establish standards for semantic consistency and data quality checks.
- Hybrid Semantic Layer (Graph + Logic): Design a hybrid semantic layer that combines graph context with business logic for enhanced search and knowledge contextualization. Model RACI/RBAC as graph edges/nodes, embedding compliance rules for auditability.
- APIs, Patterns & Collaboration: Define clean API layers for semantic enrichment and retrieval; deliver reference implementations. Collaborate with platform engineers for agent connectivity and tool discovery patterns. Partner with data, platform, and security teams for governance and observability.
- Quality, Performance & Governance: Set performance budgets to ensure efficient query execution and prevent issues. Establish lineage and governance artefacts like semantic catalogues and audit trails. Document standards and mentor engineers in adopting graph and semantic patterns.
What You Bring:
- A bachelor's or master's degree in computer science, Data Science, Mathematics, Engineering, or a related field.
- 7-12 years of experience in graph databases, semantic modelling, and ontology engineering.
- Expertise in query languages like Cypher, Gremlin, and SPARQL, with a strong understanding of LPG vs RDF/OWL tradeoffs.
- Hands-on experience with Neo4j, AWS Neptune, TigerGraph, or Stardog in a production environment.
- Proficiency in mapping enterprise data (Snowflake, MongoDB, SharePoint, ERP) into graph and ontology layers.
- A solid grasp of RBAC/RACI, data governance, lineage, and security controls.
- Ability to design clean APIs for semantic enrichment and retrieval.
- Familiarity with AWS services (IAM, VPC, S3, EKS/ECS/Lambda) in collaboration with platform teams.
Preferred Qualifications:
- Experience with ontology tooling (Protégé, SHACL/SWRL) and reasoning engines.
- Prior delivery of enterprise knowledge graphs supporting workflows and audit trails.
- Exposure to vector retrieval and how graph context informs data re-ranking.
- Knowledge of observability tools like OpenTelemetry, Prometheus, and Grafana.
Why Join Us?
This is your opportunity to be at the forefront of data innovation in the energy sector! If you are eager to make a significant impact and collaborate with talented professionals, we want to hear from you! Apply now and embark on a journey to redefine how data drives decision-making in our client's organisation. Let's build a smarter future together!
How to Apply: If you're excited about this opportunity and believe you're a great fit, please answer screening questions during application and submit your CV. Join our client and help shape the future of data engineering! We can't wait to welcome you aboard!
Candidates will ideally show evidence of the above in their CV to be considered. Please be advised if you haven't heard from us within 48 hours then unfortunately your application has not been successful on this occasion, we may however keep your details on file for any suitable future vacancies and contact you accordingly. We use generative AI tools to support our candidate screening process. This helps us ensure a fair, consistent, and efficient experience for all applicants. Rest assured, all final decisions are made by our hiring team, and your application will be reviewed with care and attention.
Semantic Graph & Ontology Architect in London employer: Adecco
At Adecco, we pride ourselves on fostering an inclusive and dynamic work culture that empowers our employees to thrive. As a Semantic Graph & Ontology Architect, you will have the opportunity to work remotely while collaborating with talented professionals in the energy sector, driving innovation and shaping the future of data architecture. We offer competitive rates, a commitment to employee growth, and a supportive environment where your unique skills and experiences are valued.
StudySmarter Expert Advice🤫
We think this is how you could land Semantic Graph & Ontology Architect in London
✨Tap into Online Data Science Communities
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We think you need these skills to ace Semantic Graph & Ontology Architect in London
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Adecco, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Adecco, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Adecco’s attention and show the tangible impact of your work.
How to prepare for a job interview at Adecco
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Adecco.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Adecco.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Adecco.
