Key Responsibilities:
- Support neo4j database administration and managing the underlying Linux environment.
- Collaborate with business and analytics teams to design and implement graph data models aligned with business use cases.
- Assist in deploying and integrating advanced analytics models.
- Develop automation scripts using Python and Shell to support data transformation and model deployment.
- Leverage AWS services for data movement, transformation, and model hosting as needed.
Key Requirements and Technology Experience:
- Key skillls; Neo4j, AWS, Docker
- Graph Data & Modelling:
- Strong experience with database onboarding (neo4j) and graph schema design.
- Ability to translate complex business logic into graph structures.
- Experience with managed graph database platforms.
- Exposure to containerized environments (Docker, Kubernetes) for model deployment.
- Familiarity with observability tools and performance monitoring for data pipelines and models.
- Cloud & Platform Knowledge:
- Familiarity with AWS services relevant to data and model operations.
- Understanding of cloud-native data workflows and security practices.
- Model Deployment & Analytics Integration:
- Experience supporting deployment of machine learning or advanced analytics models.
- Familiarity with model lifecycle management and integration into production environments.
- Harness, GitHub, GitHub actions.
- Data Engineering & Scripting:
- Proficient in Python and Shell scripting for automation and data workflows.
- Experience with ETL tools and orchestration frameworks