Data Engineer (Knowledge Graph) Offline

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.