Backend Engineer at LogSpend (Full-time) 1. Who we are LogSpend is building the self-serve analytics platform for AI-native products. We recognize that building LLM products is hard and so we help product teams get an in-depth view of how their users are interacting with their products so they can build the best AI-powered user experiences. The next frontier of user experiences will be AI-powered and our mission is to accelerate this transition into an AI-first world by enabling companies to create more value for their customers and end users through delightful AI-powered experiences.
LogSpend equips product teams with the superpowers to go beyond tracking explicit user actions to gleaning insights from unstructured user interaction and navigation data. We do this by simplifying complex data collection and reconciliation from multiple sources to ensure high-quality data at the source, automating insight extraction at scale and providing full flexibility on how these insights are consumed and acted upon by product teams. We've processed over 100M user interactions to date and serve several data-driven and AI companies. If you're excited about the potential to redefine what the future of data-driven organizations should look like in an AI-first world, then you just might have found your band! We are a VC-backed company built by two founders who spent the last 6 years at Spotify shipping personalized listening experiences to millions of Spotify users globally.
2. About the role We are in search of a proficient Backend Engineer eager to take on the challenge of managing integrations, maintaining SDKs, and overseeing the backend infrastructure essential for our analytics platform. The ideal candidate will excel in creating efficient, scalable, and low-latency integrations with various providers and tools, such as Langchain, to ensure the delivery of top-notch insights to our stakeholders.
Key Responsibilities Integration Development: Design and upkeep integrations with a variety of data sources and sinks, including BigQuery, to facilitate uninterrupted data flow and access. Data Ingestion: Work closely with data engineers to enhance data ingestion, optimizing the handling of unstructured and event tracking data in real-time. Infrastructure Scaling: Develop a robust backend infrastructure capable of managing vast volumes of tracking data, prioritizing system performance and reliability. Data Modeling: Apply data modeling strategies to offer quick, configurable insights, enabling self-serve analytics on top of NoSQL or analytics databases like Cassandra, ClickHouse and Druid. Data Visualization Support: Contribute to the creation of dynamic data models that underpin interactive graphs and data visualization on the platform. Qualifications Educational Background: Bachelor's degree in Computer Science or related field. Backend Expertise: Demonstrable experience in backend development, with a particular focus on integrations and data infrastructure.
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