Principal Data Engineer - Neo4J

Job summary

Description Principal Data Engineer – Graph Data Engineering Neo4j Role Summary As Principal Data Engineer, you will be chartered with developing functional systems to realize key business objectives and goals, with a specialization in graph data engineering and connected data architecture.

Benefits

Qualifications

• 8+ years of experience in data engineering, including experience leading engineers and technical teams
• Proven experience implementing Neo4j in enterprise environments
• Familiarity with machine learning and AI techniques leveraging graph data
• Experience working in Agile environments and leading cross-functional delivery teams
• Experience with visualization and BI
• performance and capability.
• BACKGROUND CHECK
• Results of the background check are individually reviewed based upon legal
• imposed by our regulators and with consideration of the nature and gravity of the background history and the job offered.
• Any offer of employment will include further information.

Responsibilities

• As Principal Data Engineer, you will be chartered with developing functional systems to realize key business objectives and goals, with a specialization in graph data engineering and connected data architecture.
• You will help lead a team of data engineers as you create interfaces, graph models, and data platforms that facilitate the flow, linkage, and contextualization of information across Cit***’ business operations.
• Serve as a key contributor in designing and delivering graph data solutions, partnering with stakeholders to translate business needs into connected data models and graph architectures
• Engineer and maintain graph database Neo4j, alongside relational and non-relational systems to support hybrid data environments
• Develop and operationalize relationship-based data models, including nodes, edges, and properties aligned to enterprise business domains
• Design and implement knowledge graphs and connected data platforms that unify disparate data sources and expose relationships across systems
• Build and optimize graph ingestion pipelines for batch and streaming data sources, ensuring data freshness and integrity
• Develop mechanisms and architectures that support business line specific use cases
• Establish standards and best practices for graph modeling, schema evolution, and governance within the enterprise data ecosystem
• Review and manage interfaces supporting graph data access including APIs, visualization

Skills

Degrees

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