Staff Software Backend Engineer

Working experience with property graphs/graph databases (Neo4j preferred)
Expertise with tuning and scaling Graph databases (Neo4j preferred)
Expertise with graph data models (LPG, RDF) and graph languages (Cypher, Gremlin, SparQL) with hands-on graph data modeling techniques for common use cases
Solid understanding of graph data modeling, graph schema development, graph data design
4 years + / or track record of developing graph algorithms, optimizing complex queries, designing indexes and constraints
Expertise developing APIs using property graph data
Proficiency in designing and building highly scalable Graphs in production
Competence with building data pipelines using distributed data processing frameworks
Messaging/Streaming Technologies (NATS, Kafka, AWS SQS or Kinesis), Relational and NoSQL databases (Elasticsearch, Object Storage, Graph database) and APIs
Solid understanding of developing highly scalable distributed systems using Go or Java
Competence with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools

Build Graph database platform leveraging large-scale datasets to solve various use cases
Lead design and development of graph database models to support a variety of use cases including property graphs
Design and build graph database ingestion pipeline while being the owner of the integrity of graph models and schema platform-wide
Build both batch and real-time update processes to keep the knowledge graphs in sync
Build Graph database query services in the distributed system architecture
Collaborate across product engineering teams to use existing data assets in the property graph and to drive the creation of additional data assets
Resolving technical roadblocks and mitigating potential risks
Delivering system automation by setting up continuous integration/continuous delivery pipelines

Experienced database engineer with expertise in Graph database and Big data implementation
Someone with abilities to translate various use cases to effective data modeling
Hands-on experience with database and integration (read/write) in high volume, velocity, and variety (3Vs) environment
Able to work with engineering teams for data sourcing and standards