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Graph Data Engineer
Job description
Graph Data Engineer - Dublin - HIRING ASAP
Start date: ASAP
Duration: 5 Months
Location: Hybrid Working: Dublin office
Rate: FLEXIBLE
Responsibilities
Our client is looking for a Graph Database AI/ML Engineer to work on an exciting project involving Graph Database and AI Models.
As a Graph Database AI/ML Engineer, you'll be at the forefront of innovative technology, combining the power of graph databases with machine learning techniques. Your role will involve designing, implementing, and optimizing solutions that leverage graph data structures to enhance machine learning models and drive actionable insights.
Skills:
- 10 years' experience required.
- Experience in designing and implementing graph data models that capture complex relationships, ensuring efficient querying and traversal.
- Experience with developing applications with Python.
- Integrate graph data from various sources - internal and external.
- Experience with graph database query languages (e.g. SPARQL, Gremlin, Cypher etc)
- Required proficiency in graph databases (e.g., Graphdb, Neo4j, Amazon Neptune, JanusGraph).
- Hands on experience working with LPG/RDF
- Manage graph databases.
- Experience with graph algorithms and graph-based machine learning.
- Experience with AWS infrastructure (S3, CFTs, EC2), security and data and AI pipeline technologies (RDS/Postgres, Snowflake, Airflow) and/or practical experience.
- Experience in working in Model development and deployment lifecycle using ML infrastructure and MLOps in the Cloud (AWS preferred).
- Superior SQL skills and experience developing data transformation pipelines multiple database platforms.
- Bachelor's or master's degree in computer science, Data Science, or related field.
- You are passionate about data and technology and have experience with or an interest in AI/ML and/or the consumer experience, and healthcare technology.
- You are determined, highly motivated and a quick learner.
- You should have an analytical and consulting mentality- being fearless in asking engaging questions to help tease out requirements details and technical implementation options often from more senior team members and customers.
- Excellent verbal and written communications skills.