Graph Developer - Knowledge Management (2-7 yrs)

Position : Graph Developer

Industry : Healthcare

Job Overview :

We are seeking a skilled and motivated Graph Developer to join our team in developing and maintaining advanced Neo4J-based Knowledge Graph solutions. This role will primarily focus on leveraging graph technologies to process and integrate healthcare data, enabling deeper insights and enhancing decision-making across the organization.

You will collaborate with cross-functional teams to design, build, and optimize graph databases, data pipelines, and analytics tools, ensuring the system supports high-performance queries and seamless data integration.

Key Responsibilities :

Neo4J Development & Maintenance :

- Develop, implement, and maintain Neo4J-based Knowledge Graph solutions to address specific business requirements.

- Design and create robust graph data models to represent complex healthcare-related entities and their relationships (e.g., patients, providers, medical conditions, treatments, etc.).

- Utilize Cypher query language to create optimized and efficient queries for graph traversal, data retrieval, and analytics.

- Work on Neo4J-specific features such as Graph Data Science (GDS) algorithms, graph-based metrics, and other advanced Neo4J capabilities.

Data Integration & Pipeline Development :

- Integrate data from various structured and unstructured sources (e.g., EMRs, EHRs, databases, APIs) into the Neo4J graph database while ensuring high data quality and integrity.

- Design and develop ETL (Extract, Transform, Load) pipelines for seamless data ingestion and transformation into graph format.

- Maintain data pipelines for continuous and automated updates from various data sources, including handling incremental data loading.

Business Intelligence (BI) Visualisations :

- Build intuitive and interactive dashboards using tools like NeoDash and Bloom to provide data visualization and facilitate analytical decision-making.

- Implement real-time and batch data visualizations that allow stakeholders to explore and analyze healthcare data insights efficiently.

Graph Data Science (GDS) Algorithms :

- Implement GDS algorithms such as PageRank, Community Detection, Centrality, Shortest Path, and others to perform advanced graph analytics for healthcare insights (e.g., patient network analysis, drug interaction analysis).

- Work with stakeholders to identify key use cases and provide actionable insights through graph-based metrics.

Cypher Query Optimization & Performance Tuning :

- Continuously optimize Cypher queries to ensure efficient performance, particularly for large-scale, high-volume healthcare datasets.

- Perform regular performance tuning of Neo4J instances to meet requirements for low-latency, high-throughput, and real-time data processing.

Data Analysis & Insights Generation :

- Perform advanced graph-based data analysis to identify patterns, trends, and correlations that can drive actionable insights in the healthcare domain.

- Work closely with business analysts and healthcare stakeholders to translate graph analytics findings into actionable recommendations for improving healthcare outcomes, operational efficiencies, and patient care.

Documentation & Knowledge Sharing :

- Maintain detailed, up-to-date documentation on graph data models, Cypher queries, ETL workflows, and system architecture to ensure knowledge continuity.

- Provide clear, concise documentation of new features and updates to Neo4J solutions for technical teams and business stakeholders.

Collaboration & Stakeholder Management :

- Work collaboratively with cross-functional teams (including data scientists, software engineers, business analysts, and product managers) to define and implement graph-based solutions that align with business goals.

- Engage with clinical teams, data scientists, and business stakeholders to understand healthcare-specific challenges and how graph technologies can solve complex problems.

Troubleshooting & Support :

- Diagnose, troubleshoot, and resolve issues related to Neo4J databases and performance.

- Provide ongoing support and maintenance to Neo4J solutions, ensuring reliability and stability for end-users.

Continuous Learning & Improvement :

- Stay up-to-date with the latest trends and advancements in Neo4J, graph database technologies, and data science algorithms.

- Continuously evaluate and recommend improvements to existing systems, processes, and methodologies.

Scalability & System Performance :

- Enhance the performance, scalability, and reliability of Neo4J-based systems to support high-volume and high-speed data processing in a fast-paced healthcare environment.

- Ensure that graph-based systems can handle growing datasets, complex queries, and real-time data streams.