Job Specifications
About Neo4j
Neo4j is the leader in Graph Database & Analytics, helping organizations uncover hidden patterns and relationships across billions of data connections deeply, easily, and quickly. Customers use Neo4j to gain a deeper understanding of their business and reveal new ways of solving their most pressing problems. Over 84% of Fortune 100 companies use Neo4j, along with a vibrant community of 250,000+ developers, data scientists, and architects across the globe.
At Neo4j, we're proud to build the technology that powers breakthrough solutions for our customers. These solutions have helped NASA get to Mars two years earlier, broke the Panama Papers for the ICIJ, and are helping Transport for London to cut congestion by 10% and save $750M a year. Some of our other notable customers include Intuit, Lockheed Martin, Novartis, UBS, and Walmart.
Neo4j experienced rapid growth this year as organizations looking to deploy generative AI (GenAI) recognized graph databases as essential for improving it's accuracy, transparency, and explainability. Growth was further fueled by enterprise demand for Neo4j's cloud offering and partnerships with leading cloud hyperscalers and ecosystem leaders. Learn more at neo4j.com and follow us on LinkedIn.
Our Vision
At Neo4j, we have always strived to help the world make sense of data.
As business, society and knowledge become increasingly connected, our technology promotes innovation by helping organizations to find and understand data relationships. We created, drive and lead the graph database category, and we're disrupting how organizations leverage their data to innovate and stay competitive.
The Team
The Data Importer team builds the Neo4j Data Importer application that helps our users connect to and create graphs from any type of structured or unstructured data sources - databases, data warehouses, files, web pages, etc. It is a great place to start when just getting into graphs, but will also be able to handle large amounts of data for more advanced setups. Once connected, Data Importer will suggest a graph model for you. You make any edits to the data mapping before starting your import jobs.
In order to deliver this experience, the team works closely with Product Management, UX and Test, as well as other teams such as Connectors, GenAI, Core Database and Cloud teams. The team consists of 6 engineers located in Malmo and London.
The Role
As a Full Stack Software Engineer in the Data Importer team you will be contributing to our cloud-based low-code importing tool, and orchestrating features across the developmental stack to bring new features to thousands of users across the globe. Working closely with designers, product managers and other teams, you'll be:
Prototyping new and experimental features
Improving UI components and graph visualisations
Leveraging cutting edge AI technologies
Delivering robust solutions to customers
Coordinating with backend teams to integrate data import services
Production experience with several of the technologies we use is desirable but not essential. You should have strong Javascript/Typescript skills. Our services layer is Go and Kotlin-based so you should know one of them well, or be interested in picking it up. Our engineers work in both our Malmo and London offices and most teams are split across the two, so you must be comfortable working as part of a distributed team. We use extensive automated testing, so proficiency with a range of approaches from unit testing up to full-stack integration testing will be helpful.
The Technologies We Use Most Are
JavaScript/TypeScript and React in the Browser
Kotlin, Go, Docker, and Kubernetes on the server
GCP, AWS, and Azure
About the Company
Neo4j, the Graph Database & Analytics leader, helps organizations find hidden relationships and patterns across billions of data connections deeply, easily, and quickly. Customers leverage the structure of their connected data to reveal new ways of solving their most pressing business problems with Neo4j’s full graph stack and a vibrant community of developers, data scientists, and architects across hundreds of Fortune 500 companies.
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