Data Engineer (Knowledge Graph)

About the Project We are building a system that integrates multiple databases and external APIs, aggregates data from various sources, and constructs a real-time knowledge graph to track complex relationships between entities.

Key Requirement ‼️ Hands-on experience with graph databases (minimum 6 months) is mandatory. We are specifically looking for candidates who have practical experience with graph data modeling and writing queries.

Tech Stack Graph Databases, Neo4j, Python, FastAPI, SQL, NoSQL, Docker, Docker Compose.

Responsibilities — Design, build, and maintain scalable data pipelines — Develop and optimize graph-based data models (nodes, edges, properties) — Build and maintain a real-time knowledge graph — Integrate multiple data sources (APIs, SQL, NoSQL databases) — Optimize graph queries and data processing performance — Work with cloud infrastructure (AWS) — Collaborate with backend and product teams to design data solutions — Build proof-of-concept solutions involving graph technologies

Requirements — 3+ years of experience as a Data Engineer / Backend Engineer (data-heavy projects) — Hands-on experience with graph databases (Neo4j, ArangoDB, Amazon Neptune, etc.) — Strong knowledge of SQL and NoSQL databases — Experience building data pipelines and working with large datasets — Good understanding of data modeling (especially graph structures) — Experience with AWS or other cloud platforms — Python proficiency — English (from Upper-Inermediate)

Nice to Have — Experience with knowledge graphs — Experience with streaming or real-time data processing — Background in Computer Science, Mathematics, or related field — Experience with recommendation systems / analytics / fraud detection

Who will succeed in this role Someone who enjoys working with complex data relationships, understands how to model real-world systems as graphs, and can bridge backend engineering with data engineering practices.