Luca Tabone

September 2024 - Present

Developing the backend of an AI powered internal tool used by all 4.000 Klarna employees
The tool certifies every Klarna employee anually on different topics around compliance and worldwide financial regulations
We embedded an AI powered chatbot to help employees with their get certified
100 % Hands-On Backend Engineering with Python
Daily work includes technologies like Python, Docker, PostgreSQL, FastAPI, REST, CI/CD, Multi-Processing, Async Programming, Web Scraping, Selenium
I worked in a small team with 2two other AI/Backend engineers and one Frontend engineer

December 2023 - Present

Leading the development of the Backend of the German startup Mirror Health (now Sugar Helath)
100 % Hands-On Backend Engineering with Python
Daily work includes technologies like Python, Docker, Kubernetes, AWS, PostgreSQL, MongoDB, FastAPI, REST, Kafka, CI/CD, Multi-Processing, Multi-Threading, Async Programming
Working cross-functionally with the Product-, Design-, Frontend- and DevOps Team to ensure consistent alignment across the projects lifetime

July 2022 - Present

Built a web-scraping system to parse Website data to structured JSON.
Built a web-crawling and scraping system that enables us to scrape social platforms using mobile proxies.
Created the local-storage-architecture of our Next.js EagleEye app using Zustand
Drove the effort to change the Tech-Stack of our EagleEye web-app from (multi-repo, Node.js, JavaScript, GraphQL and React) to a monorepo based t3-stack (Next.js in the backend and frontend, TailwindCSS, tRPC as a type-safe API layer, Prisma ORM). This led to faster iteration cycles during the development of EagleEye and fewer engineers needed to further build and maintain the app.
Implemented the tRPC API endpoints for our web-app.
Lead the hiring of 7 engineers.
Lead the bi-weekly sprint plannings and quarterly OKR plannings.
Stakeholder Management. Consolidating feedback and ideas from our general Partners and making sure to deliver on deadlines.
Designed dozens of database models for our PostgresDB.
Conducted User Interviews for our web-app.
Driving UX decisions based on user feedback.
Integrated all software projects within the Earlybird technology department into a monorepo.
Lead the development of a programming-language agnostic code-library with our monorepo.

February 2021 - June 2022

Created a React & Node.js based webapp to enable the inbound logistics team to handle and update product stock across various online shops.
Built a Python pipeline that automatically handles exchange cases and saves OCEANSAPART more than 1.1 million € each year.
Python pipeline that automatically handles refund cases. This task was previously also handled by a third party involving human agents to process refund cases. The pipeline I built for handling > 50 % of all refund cases automatically helped to save > 400k € each year.
Python pipeline to keep the product pictures of our online shops in sync with the Google Drive folder of the Design team.
Python pipeline to handle automatic emails to keep customers up-to-date on shipping information regarding their orders.
Python pipeline to programmatically apply discounts to our products.
Python pipelines to aggregate information on our ad-spent across the platforms (Instagram, Snapchat, TikTok, Facebook) and sync this data with a Google Sheet used by the C-Levels of the company which they used to assess our marketing performance.

January 2020 - January 2021

Built a mobile app in React-Native that enables coffee shops and restaurants to accept credit card payments and reward their customers loyalty with a digital stamp-card system.
Built a second mobile app in React Native for the customers of the shops which allowed them to view their digital stamp-card wallet and load their loyalty cards with money using Apple- or Google-Pay.
Built the REST based serverless Python API with Flask for the two mobile apps. The API was deployed to Google Cloud Run.
Built the Postgres Database on Google Cloud SQL.
Our user (the customer of a coffee shop) would earn a stamp by getting their QR code scanned in the shop. In order to provide the user with feedback on the stamp they just earned, I integrated the Realtime Database of Google Firebase into the backend and into both mobile apps.

July - December 2019

During my 6 months at Netlight I consulted the finance department of one of our clients in the automotive industry on data visualisation using Looker.
Hands-On supported the engineering teams on further developing the Java based backend that processes card payments on our clients site.

September 2017 - Juni 2019

Given a tree of depth level 10 where each node represents an industry, e.g. mobility or energy, I developed a net of 142 interconnected Multi-Layer-Perceptron's to solve hierarchical text categorisation. We achieved a classification accuracy of 96.7 %.
The text data used to train the supervised model mentioned above, was scraped from 10 different sources. I implemented a headless Selenium scraper deployed on Google Compute Engine to continuously scrape these sites.
Built various Data Engineering Pipelines for our SQL database.

Hi, I'm Luca.