Knowledge Graph Engineer

Wissen Technology is hiring for Knowledge Graph Engineer

About Wissen Technology:

At Wissen Technology, we deliver niche, custom-built products that solve complex business challenges across industries worldwide. Founded in 2015, our core philosophy is built around a strong product engineering mindset—ensuring every solution is architected and delivered right the first time. Today, Wissen Technology has a global footprint with 2000+ employees across offices in the US, UK, UAE, India, and Australia. Our commitment to excellence translates into delivering 2X impact compared to traditional service providers. How do we achieve this? Through a combination of deep domain knowledge, cutting-edge technology expertise, and a relentless focus on quality. We don’t just meet expectations—we exceed them by ensuring faster time-to-market, reduced rework, and greater alignment with client objectives. We have a proven track record of building mission-critical systems across industries, including financial services, healthcare, retail, manufacturing, and more. Wissen stands apart through its unique delivery models. Our outcome-based projects ensure predictable costs and timelines, while our agile pods provideclients with the flexibility to adapt to their evolving business needs. Wissen leverages its thought leadership and technology prowess to drive superior business outcomes. Our success is powered by top-tier talent. Our mission is clear: to be the partner of choice for building world-class custom products that deliver exceptional impact—the first time, every time.

Job Summary: We are seeking an experiencedKnowledge Graph Engineer(4–8 years) to design and implement enterprise‑scale knowledge graphs that unify data across domains such asiShield, TPAD, COC, and TPPM. The ideal candidate will have strong hands‑onexpertisein graph technologies (RDF/OWL or Property Graph), ontology and schema design, data engineering pipelines, and performance optimization. This role focuses on building ingestion pipelines,optimizinggraph queries, and exposing graph‑derived datasets to downstream systems such as Snowflake, Power BI, andDataZone.

Key Responsibilities:

• Design and implemententerprise knowledge graphsacross multiple business domains.
  
• Build ingestion pipelines to instantiateentities, relationships, and semantic constraints.
  
• Optimizegraph queries, indexing, labeling strategies, and reasoning workflows.
  
• Publish graph‑derived datasetstoSnowflake, Power BI, andDataZone.
  
• Productionizereusable graph query packsfor analytics and data consumers.
  
• Implement ontology/schema design, identity resolution, and relationship modeling.
  
• Work with batch/streaming ETL pipelines usingPython, Spark/Lightning, APIs, and structured formats (JSON/CSV/Parquet).
  
• Ensure performance, observability, and monitoring for graph workloads.
  
• Package datasets for secure consumption with properAuthN/Z and row/column‑level controls.
  
• Collaborate with engineering, data, and platform teams to integrate graph systems into enterprise workflows.
  
  

Required Skills and Qualification


• Graph Technologies
  
• Strong hands‑on experience withRDF/OWL/SPARQLorProperty Graph (Neo4j/TinkerPop)ecosystems.
  
• Proficiency withCypher, Gremlin, and graph databases likeGraphDB,Fuseki, Neptune, Neo4j.
  
• Modeling & Semantics
  
• Expertise inontology design, schema modeling, SHACL/SHEX constraints, and identity resolution.
  
• Strong understanding of relationship modeling and semantic structures.
  
• Data Engineering
  
• Python programming; Spark/Lightning ETL; REST APIs.
  
• Experience working withJSON, CSV, Parquet, and CI/CD pipelines.
  
• Experience with batch and streaming data ingestion.
  
• Performance & Operations
  
• Hands-on experience inquery tuning, indexing, caching, and observability/monitoring.
  
• Understanding ofenterprise‑grade deployments and optimization workflows.
  
• Integration
  
• Ability to publish graph slices toSnowflake, andprepare datasets forDataZoneincluding row/column‑level security.
  

Good to have Skills


• Experience withreasonerssuch asHermiTor ELK.
  
• Exposure to text‑to‑graph extraction, NLP‑assisted data modeling, or knowledge fusion.