Graph Database Engineer

Title: Graph Database Engineer
Location: 100% Remote

Duration: 12+Months

Must have skills:
Graph data modelling (Experience with graph data models (LPG, RDF) and graph languages (Cypher, Gremlin, SparQL), exposure to various graph data modelling techniques)
Optimizing complex queries
AWS

The Expertise You Have

• Bachelor's or Master's Degree in a technology related field (e.g. Engineering, Computer Science, etc.).
• Demonstrable experience in implementing Big data solutions in data analytics space.
• Hands-on experience with graph databases (Neo4j, or any other).
• Experience Tuning Graph databases
• Understanding of graph data model paradigms (LPG, RDF) and graph languages (Gremlin & SparQL are optional), hands-on experience with Cypher is required
• Solid understanding of graph data modeling, graph schema development, graph data design.
• Desirable (Optional) skills:
• Data ingestion technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologies.
• Understanding of developing highly scalable distributed systems using Open-source technologies.
• Experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent).
• Experience in Agile methodologies (Kanban and SCRUM).

The Skills You Bring

• You the ability to deal with ambiguity and work in fast paced environment.
• Your experience supporting critical applications.
• Your Data wrangling experience with structured, semi-structure data.
• You have superb communication skills, both through written and verbal channels.
• You have excellent collaboration skills to work with multiple teams in the organization.
• Your ability to understand and adapt to changing business priorities and technology advancements in Big data and Data Science ecosystem.

The Value You Deliver

• Build Graph Database solutions leveraging large-scale datasets to solve various business use cases.
• Design and build graph data models to support variety of use cases including knowledge graphs
• Design and build graph database load processes to efficiently populate the graph database
• Use AWS to host and manage the knowledge graphs is desirable
• Build both batch and real-time data ingestion processes
• Collaborate across Data Platform teams to use existing data assets and drive the creation of additional data assets
• Guiding teams to improve development agility and productivity.
• Resolving technical roadblocks and mitigating potential risks.
• Delivering system automation