Data Engineer Neo4J

AVN Digital Pte Ltd is a reputed global IT professional services company headquartered in Singapore. Our service spectrum includes enterprise solution consulting, business intelligence, business process automation and managed services. We serve a client base across banking and financial services, insurance, information technology, healthcare, retail and supply chain.

Responsibilities

• Model Complex Banking Data in Neo4j: Design and implement graph data models representing customers, accounts, transactions, devices, and their interconnected relationships.
• Apply Graph Data Science (GDS) Algorithms: Leverage Community Detection, Link Prediction, Node Embeddings, and Pathfinding algorithms to uncover hidden fraud patterns and suspicious networks.
• Build Real-Time Investigation Dashboards: Develop interactive visualisations using Neo4j Bloom to empower Risk and AML teams with actionable insights.
• Collaborate Across Teams: Partner with Risk Management, Anti-Money Laundering (AML), Compliance, and Data Science teams to translate business requirements into technical solutions that reduce fraud losses.
• Optimise Performance: Ensure scalability, performance tuning, and reliability of graph databases in production environments.
• Drive Innovation: Stay current with emerging graph technologies and fraud detection techniques, and contribute to continuous improvement of analytics capabilities.

Qualifications

• Must-Have: 5–6 years of overall IT experience, with 2+ years of hands-on experience working with Neo4j, Cypher query language, and Graph Data Science (GDS) library.
• Strong proficiency in Python for ETL pipelines, data processing, and integration with Neo4j GDS workflows.
• Solid understanding of graph database concepts, including data modelling, indexing, query optimisation, and performance tuning.
• Experience applying GDS algorithms such as Community Detection (Louvain, Label Propagation), Link Prediction, Node Embeddings (Node2Vec, GraphSAGE), and Centrality measures.
• Familiarity with Neo4j Bloom or similar graph visualisation tools for building investigative dashboards.
• Experience in the Banking, Fraud Detection, or AML domain is highly preferred.
• Strong analytical and problem-solving skills with the ability to translate complex business requirements into technical solutions.
• Excellent communication and collaboration skills to work effectively with cross-functional teams.
• Good-to-Have: Experience with other graph databases (e.g., Amazon Neptune, TigerGraph, JanusGraph).
• Knowledge of machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and integrating ML models with graph analytics.
• Familiarity with cloud platforms (AWS, Azure, GCP) and deploying Neo4j in cloud environments.
• Understanding of data streaming technologies (Kafka, Kinesis) for real-time fraud detection pipelines.
• Experience with CI/CD pipelines, Infrastructure as Code (Terraform, CloudFormation), and DevOps practices.
• Knowledge of regulatory frameworks related to AML, KYC, and financial crime compliance.
• Neo4j Certified Professional or Graph Data Science certification is a plus.
• Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, or a related field.
• 5-6 years of experience in IT production, preferably in banking or financial services.
• Good problem-solving skills and ability to work under pressure in a fast-paced environment.
• Strong communication skills with the ability to liaise effectively across teams.

What’s on Offer

• You will be remunerated with an excellent base salary and entitled to attractive company benefits.
• Opportunity to enjoy a fun and collaborative work environment, alongside strong career progression.