Overview
On Site
Depends on Experience
Full Time
Skills
Algorithms
Data Integration
Data Analysis
Data Modeling
Data Visualization
Data Warehouse
Database
Conflict Resolution
Extract
Transform
Load
Graph Databases
Neo4j
Python
SQL
Tableau
Job Details
Must have:
- Graph database expertise: A deep understanding of graph database concepts and proven experience with Neo4j is crucial.
- Query languages: Strong proficiency in the Neo4j query language, Cypher, is required.
- Programming languages: Skills in Python or Java are often needed for scripting data ingestion, automation, and integrating with other systems.
- Analytical skills: Excellent problem-solving, critical thinking, and analytical abilities for interpreting complex datasets.
- Data warehousing: Experience with cloud data platforms and other databases, including traditional SQL, is often necessary for data integration.
- Data visualization: Experience with data visualization tools like Tableau or Power BI is valuable for presenting findings clearly.
- Domain knowledge: An understanding of the business domain, such as finance or healthcare, is important for contextualizing data and analysis
Roles & Responsibilities:
- Graph data modeling: Design and refine the structure of data as nodes and relationships within a graph database to best serve specific analytical needs.
- Data ingestion and processing: Build data pipelines to extract, transform, and load (ETL) data from various sources into the Neo4j graph database.
- Cypher query development: Write and optimize complex Cypher queries to explore data patterns, find connections, and perform deep-link analysis.
- Graph algorithm implementation: Apply graph algorithms (e.g., centrality, community detection, pathfinding) to answer complex business questions related to network structures.
- Data analysis and visualization: Perform exploratory analysis and create dashboards, reports, and data visualizations to communicate findings to both technical and non-technical stakeholders.
- Collaboration: Work with other teams, including data scientists, data engineers, and business leaders, to understand data requirements and deliver actionable insights.
- Maintenance and performance tuning: Monitor the performance of Neo4j queries and the overall database and make adjustments for efficiency and scalability.
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