Capto HR

Compensation

Full Description

bubbi.ai is a fast-growing Swedish AI technology company that helps leading e-commerce companies create personalized customer experiences in real time. Using advanced data analytics, tracking and AI, we understand every customer journey and optimize the experience for maximum relevance. Our customers include players such as Lyko, Jula, Synsam, Apollo, Kids Brand Store and Besikta Bilprovning. We are a remote-first company that works agilely in shorter sprints with a dedicated and fast-paced team of developers, AI specialists and project managers. We are now facing an exciting growth journey, both in Sweden and internationally – and are looking for you who want to be an important part of that journey! Read more about us at www.bubbi.ai Bubbi.ai are looking for a Junior Data Engineer Help us reinvent how ecommerce operators draw insights from their data. As a Junior Data Engineer at Bubbi you will help ship a brand-new product, based on AI and large amounts of behavioural data, that turns natural-language questions into trusted, actionable insights for our clients. We’re creating a new analytics engine for ecommerce using the latest LLMs on top of BigQuery with a Python/FastAPI service layer. We need an intelligent fast learner who can get hands on to put the development pace into next gear. It’s a chance to join early and be part of a small, fast-paced team where you can shape both the product and how we work. What you’ll do You will develop next-generation analytics solutionsthat power smarter e-commerce decisions by applying the latest AI modelsto deliver value-creating solutions for our clients. In your work you will extend and tidy FastAPI endpoints for analytics access, expose selected KPI metrics via API. The role contains build and maintain SQL transformations for user-events, you will propose partitioning/clustering and retention. Besides working with the product development you will: Client Onboarding analysis: run the initial customer analysis and further develop it and standardize it Add observability, logging, basic metrics, alerts, and simple SLOs Product monitoring: set up KPI tracking, run QA during launches, and continue monitoring post-launch Tracking QA (web & app): validate event schemas, identity/session logic, issue a documented green-light for analysis Dashboards: Continued backend development Pipelines: schedule/monitor nightly jobs; validation tests, and simple performance follow-up Minimum qualifications Master’s in Engineering/Computer Science (early-career welcome). Solid Python and pandas; basic Git/GitHub. Comfortable with SQL (BigQuery a plus): can review/adjust AI-generated queries and reason about bytes scanned/performance. Willing to learn FastAPI/Pydantic and Docker quickly. Uses AI coding assistants effectively with a verification mindset. Basic understanding of tracking (events, sessions) and reproducibility in analytics. Nice to have BigQuery basics (datasets, partitions, clustering) Cloud Run or similar; simple caching layers Cloud Logging/Monitoring; Looker/Looker Studio Basic experimentation concepts (exposure/assignment, metric definitions; light stats literacy) Schema versioning and data contracts, simple auth/access patterns (tokens, service accounts) Personal attributes You have to be a fast learner and curious and you will quickly adapt to new technologies and environments to start creating value. You must be systems thinking and used to structure, working with checklists, basic SLO/SLA when needed. You are a clear communicator and have documentation habits. Tech stack GCP BigQuery, Python/FastAPI, pandas, Docker, Git/GitHub, competence in Cloud Run, Cloud Logging/Monitoring is good to have and you should have used OpenAI API models. The work is fully remote.