About Cerebre
cerebre is on a mission to build the data foundation of the physical world. We offer a live intelligence map of a facilities built from schematics to power AI. Often called the brain of the digital twin, cerebre helps engineers, data scientists, and business teams understand data within the context of the plant.
We collaborate with the world's largest companies and most innovative partners who are transforming the industrial sector.
cerebre is a global team of engineers, scientists, innovators, and explorers united by a mission to help the world's largest manufacturing facilities build and use intelligence.
Our development team is made up of world-class engineers who design and deliver novel solutions. This is an opportunity to join a market-leading team that is changing how the industrial world works.
If you love building and creating value in the white space, if you thrive with the freedom and flexibility to think outside the box, if you are passionate about working with critical thinkers who challenge the status quo, and if you aspire to work in a fast-paced environment we would love to meet you!
We believe flexibility drives creativity and that our team should live and work where we can be our best selves. We're 100% remote and offer a competitive time-off package to ensure time for rest and recharge.
About The Role
We are seeking a Data Engineer with expertise in graph data systems to design, manage, and query large-scale knowledge graph datasets. In this role, you will focus on structuring and optimizing queries for complex industrial and operational data that power advanced analytics across our platform.
The ideal candidate brings strong experience with graph databases (Cypher or similar query languages) and enjoys collaborating with engineers and domain experts to translate real-world systems into scalable, well-structured data models.
We are looking for a curious and adaptable engineer who enjoys learning new domains and working with complex data systems. The right candidate will combine strong data engineering fundamentals with an exploratory mindset, allowing them to quickly understand new engineering concepts and translate them into scalable, graph-based data models.
Key Responsibilities
- Write and optimize Cypher (or similar) queries to extract and analyze complex relational data
- Develop graph data models, ontologies, and schema structures
- Translate industrial and operational data into structured graph representations
- Work closely with software engineers, product teams, and domain experts to define data requirements and outputs
- Maintain strong data governance, security, and compliance standards
- Improve graph performance, scalability, and data infrastructure as datasets grow
Required Skills
- 4+ years of relevant experience
- Experience working with graph databases / knowledge graphs
- Strong proficiency with Cypher or similar graph query languages
- Experience managing and querying large, complex datasets
- Strong data modeling and schema design capabilities
- Familiarity with secure and compliance-sensitive data environments
- Experience interacting with REST APIs for data ingestion, integration, or automation
- Proficient in the English language
Preferred Skills
- Industrial sectors such as Energy, Oil & Gas, Infrastructure, Healthcare, or Aerospace
- Experience collaborating with engineering or operational teams to structure domain data
- Exposure to ontology design, semantic data models, or knowledge representation
- Experience working with Python for data workflows (e.g., Python scripts or notebooks)
- Experience working with ETL tools (e.g. Azure Data Studio)
More About Cerebre
We are cross-functional collaborators.
We blend manufacturing process knowledge with software and big data engineering expertise to create value in physical settings
We Are Experienced.
We are armed with industry-leading experts in numerical simulation, combustion, power, computational fluid dynamics, and chemical process modeling
We are serious builders.
We develop our platforms using leading practices in IT/OT architecture, OT security, AI architecture, ML Ops, and Platform engineering
