Senior Python Backend Data Base Engineer

We are seeking a highly skilled Graph Database Engineer with strong expertise in Python development Neo4j graph databases and backend engineering. The ideal candidate will be responsible for designing building and maintaining graph-based data solutions while developing scalable backend services and data pipelines.

The candidate should possess hands-on experience with Neo4j Cypher query development graph data modeling API integration and database performance optimization. This role requires close collaboration with data scientists analysts and engineering teams to deliver graph-powered solutions for use cases such as recommendation systems fraud detection knowledge graphs and network analysis.

• Design develop and maintain scalable backend services using Python.
• Build and manage robust data pipelines to support graph-based applications.
• Develop and maintain RESTful APIs and backend integrations.
• Ensure high-quality maintainable and reusable code through engineering best practices.

• Design and implement graph database solutions using Neo4j.
• Develop graph schemas and data models aligned with business requirements.
• Build and maintain graph structures representing complex relationships and connected data.
• Support enterprise graph-based use cases including recommendation engines fraud detection knowledge graphs and relationship analysis.

• Develop test and optimize Cypher queries for complex graph traversals and analytics.
• Implement efficient querying strategies to improve performance and scalability.
• Optimize indexing relationships and graph structures for enhanced query execution.

• Integrate Neo4j with backend services using Neo4j drivers APIs and Bolt Protocol.
• Design seamless data flow between applications APIs and graph databases.
• Collaborate with cross-functional teams to deliver end-to-end graph-based solutions.

• Monitor graph database health and performance.
• Troubleshoot database issues bottlenecks and query execution challenges.
• Perform indexing query tuning and database optimization.
• Ensure system reliability scalability and operational efficiency.

• Work closely with data scientists analysts architects and software engineers.
• Participate in code reviews and technical design discussions.
• Contribute to engineering standards best practices and continuous improvement initiatives.
• Support documentation and knowledge-sharing across teams.

• Python Development
• Backend Engineering
• RESTful API Development
• Object-Oriented Programming
• Git Version Control
• Software Development Best Practices

• Neo4j
• Graph Database Concepts
• Graph Schema Design
• Graph Data Modeling
• Relationship Modeling
• Graph Analytics

• Cypher Query Language
• Query Optimization
• Complex Graph Traversals
• Database Indexing
• Neo4j Drivers
• Bolt Protocol

• Data Pipelines
• Data Processing
• Data Transformation
• Data Integration

• Database Performance Tuning
• Query Performance Optimization
• Troubleshooting
• Monitoring
• Scalability Optimization

• Apache Airflow
• Apache Kafka
• Pandas
• ETL/Data Pipeline Frameworks
• Data Warehousing Concepts
• Cloud-Based Data Platforms
• Graph Data Science Techniques

• Recommendation Engine Development
• Fraud Detection Systems
• Knowledge Graph Implementation
• Network and Relationship Analysis
• Microservices Architecture
• Containerization (Docker/Kubernetes)
• CI/CD Practices
• Cloud Platforms (Azure AWS or GCP)

• Strong analytical and problem-solving abilities.
• Excellent communication and collaboration skills.
• Ability to work independently and manage priorities effectively.
• Strong stakeholder engagement and teamwork capabilities.
• Ability to translate business requirements into scalable technical solutions.
• Continuous learning mindset and passion for emerging technologies.

• Proven experience developing graph-based applications and solutions using Neo4j.
• Strong hands-on expertise in Python backend development and API integration.
• Experience designing and optimizing graph data models for enterprise-scale workloads.
• Knowledge of graph analytics connected data use cases and relationship-driven architectures.
• Ability to independently design implement and support production-grade graph database solutions.
• Experience working within cross-functional teams to deliver scalable and high-performing data products.