Architect a data platform for financial services client from scratch. Data Platform is design to be based on Databricks, AWS and with the mindset of Data Products, to allow scaling and ownership. Main tasks and responsibilities:

Architect a data platform for IoT Smart Metering client from scratch. Working with stakeholders, Tech Lead and Data Engineers to design the data platform that fullfills the needs, and has the flexibility to scale when the data volume grows 1000X. Main tasks and responsibilities:

Designed and architected an end-to-end MLOps platform on AWS EKS for predicting car-sharing demand across 3,700+ city hexagons in 3 cities. Built production-grade ML pipelines with automated feature engineering, model training, model versioning, and daily batch inference serving 7-day demand forecasts. Implemented comprehensive monitoring with drift detection and retraining triggers, reducing model deployment time from weeks to hours while ensuring prediction accuracy >88 % MAE. Main tasks and responsibilities:

Migrate data pipeline from a VM-based architecture in Azure, to a Scalable Architecture in AWS Managed Services using it cost-effectively. The existing data pipeline was reaching it?s limits, therefore we decided to rearchitect the whole data pipeline in a new paradigm, with scalability in mind. Volume of messages is around 10 million messages per day, with a peak at the first week of the month around 2M messages in 4 hours. Main tasks and responsibilities:

Building a platform to help indie and mid-size game publishers to figure out privacy-first mobile marketing. The goal is to enable mobile game publishers to collect data, from multiple sources, store it the way they want, and gain insights via intuitive dashboarding. The project is developed in a microservice architecture with 4 modules: Frontend, Backend, Orchestration/Pipeline, AI Predictions and Transformations. Main tasks and responsibilities:

Design and implement an ML solution that is able to perform multi-class classification of emails based on their content. Main tasks:

• Evaluate possible NLP based approaches.

Using insights gathered from the data analytics department, develop a scalable solution to connect sales consultants with leads/customers. The matching of the consultant with a lead takes into account business specific logic, defined by BI stakeholders. Main tasks and responsibilities:

Modernize the sale process for VW dealers for the new electric cars. As part of a balanced team of engineers, designers (UI/UX) and PMs, I worked closely with other colleagues to create a holistic integrated solution supporting the whole business flow of sales for VW dealers. Main tasks and responsibilities:

Ideate, design, and build a solution helping first level support to get insights about which systems are running and which ones are failing. Provide dashboards detailing the features of a system are up and the ones are down. Also store and analyse historic data, to provide feedback for stakeholders. Main tasks and responsibilities:

Develop a cloud-native solution addressing the needs of corporates in managing their real estate assets and their workspace. Main tasks and responsibilities: