At Caffeine.ai, we are building the world’s first platform where full-stack, on-chain applications are created through natural language. Our mission is to make software creation as simple as a conversation - turning ideas into live, production applications in minutes.
We are looking for a Data Analyst with strong Databricks experience to help define, aggregate, and interpret the data that powers our product and agentic Chat-to-App system. This role sits at the intersection of product analytics and data enablement.
You will ensure that the right events exist, the data model makes sense, and insights can be consumed quickly - not just by analysts, but by engineers, product managers, and leadership.
About the Role
This role goes beyond traditional dashboards. You will:
Help design and standardize our event taxonomy across frontend, backend, and AI workflows
Own how raw event streams are aggregated, modeled, and exposed in Databricks
Use AI-assisted analytics to accelerate insight generation and user journey mapping
Enable self-serve business intelligence so non-data experts can confidently explore product health and growth
You’ll work closely with Engineering, Product, SRE, and AI teams to turn high-volume system and user interaction data into trusted signals that guide product decisions and build confidence in the platform.
What You’ll Do
Define and evolve event schemas and naming conventions, guiding engineers on what to instrument and why
Build and maintain Databricks pipelines to aggregate raw event data into reliable, analytics-ready datasets
Create product funnels, cohorts, and retention analyses for the Chat-to-App lifecycle
Develop AI-augmented workflows (e.g., notebooks, summaries, automated insights) to speed up data interpretation
Build clear, accessible dashboards and reports that can be consumed by Product, Engineering, and Leadership
Translate complex datasets into concise narratives that drive product and platform decisions
Who You Are
Bachelor’s in Computer Science, Statistics, Mathematics, or a related technical field.
2–4 years of experience in Data Analytics, Product Analytics, or Business Intelligence.
Hands‑on experience with Databricks (SQL, notebooks, or similar)
Strong SQL skills and experience working with event‑driven, high‑volume datasets
Strong communication skills — able to explain data clearly to non‑technical audiences
Product‑minded: you care about why data matters, not just how to query it
Bonus
Experience designing event taxonomies or analytics instrumentation frameworks
Familiarity with observability data (logs, metrics, reliability signals)
Python proficiency for ad-hoc analysis or data tooling
Experience at an AI‑first or infrastructure‑heavy startup
This is a hybrid role based in our Zurich office, with a requirement of 3.5 days in the office per week.
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