.Job DescriptionAbout UsHarmonic is the startup discovery engine. We believe in innovation, entrepreneurs, and efficient capital markets. It pains us to see great startup opportunities consistently go undiscovered. So, we dedicated ourselves to mapping out the startup landscape and building the index and tools that ensure the most promising founders get found and funded.The world's largest and most prolific venture capital firms rely on us to find and invest in the next Google, AirBnB, Uber, Stripe, and Anduril. We play a crucial part in ensuring hundreds of billions of dollars get routed efficiently and that the innovations the world would most benefit from materialize.We've been growing steadily and need passionate driven people to help us get to the next level. If you want to work in a high-growth environment with some of the most talented folks on the planet and resonate with our values, read on.About The Discovery TeamThe discovery team is focused on making it delightfully easy for users to find the startups they're looking for. We source, transform and index terabytes of data, build models to make sense of the data, and build product experience to facilitate users actively and passively discovering startups at the right time.The roleWe are looking for an engineer to join our team and help us unlock the full potential of our most critical asset: our data. You will have direct impact on our revenue and customers by ensuring that our systems can handle the complex relationship between our entities. You will be responsible for scaling our knowledge graph infrastructure and managing our time series data. You will also evaluate and improve our data storage and taxonomy systems, and mentor and manage other engineers on the team.What you'll do:Derive deeper insight from our data by scaling our current knowledge graph infrastructure to handle hundreds of millions of datapoints.Deeply understand how our insight layer is connected to the rest of our application layer and ensure the needs of our customers and teams are met by focusing on performance, observability, and most importantly customer demand.Evaluate how we store time series data and help us scale it 10x the current throughput in an iterative manner.Leverage ML infrastructure and services to continually improve our taxonomy and derive relevant signals from the underlying data.Role requirements:5+ years of building highly performant, highly observable, and highly scalable systems.Extensive experience in search systems (search, recommendations, and knowledge graphs). Passionate about making discovery more intuitive and user-friendly.Experience with search technologies (Lucene, Elastic Search, Solr, etc).Experience with streaming technologies (Pub/Sub, Kafka, RabbitMQ, etc).Experience with various data storage solutions (SQL, NoSQL / key-value stores).Plus If...2+ years of experience in an early-stage startup