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.

<aside> 🌎 Location: Barcelona, Spain ☀️ Job type: Full-time

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👨‍👨‍👧‍👦 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 create more value for their customers and end users through delightful AI-powered experiences.

🎯  LogSpend equips product teams with the super powers 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 on the lookout for a skilled and dedicated Data Engineer to become a part of our energetic team. In this role, you'll be instrumental in crafting and maintaining a scalable data processing infrastructure that underpins our AI-driven analytics platform. Your expertise will guide the transformation of unstructured and event-based tracking data into actionable insights, working alongside our data scientists, product managers, and business teams.

Key Responsibilities

• Data Infrastructure Development: Design, develop, and maintain premier data products and infrastructure, ensuring the reliability and integrity of insights delivered to stakeholders.
• Analytics Platform Management: Build and oversee comprehensive data analytics platforms, handling everything from raw data processing to the derivation of meaningful metrics and insights.
• Integration and Optimization: Collaborate with backend engineers to seamlessly integrate data sources and sinks, like BigQuery, optimizing for efficiency and minimal latency.
• Data Modeling: Implement adaptable data modeling techniques to provide instant, configurable insights, utilizing platforms such as ClickHouse and Druid for self-service analytics.
• Cross-functional Teamwork: Work closely with various teams to uphold data quality, manage pipelines, and coordinate data processing schedules effectively.

Qualifications

• Data Processing Expertise: Demonstrated ability in creating scalable data processing infrastructures and managing unstructured and event-based tracking data using frameworks like Apache Spark and Apache Flink.
• Machine Learning Acumen: A good grasp of machine learning concepts and experience with AI-driven insights.