Florian Räuber

Experienced Senior Software Engineer at Snowflake who has a strong background in Cloud Architectures, AI, BigData, and DevOps principles.

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About me

I am a passionate software engineer with a focus on cloud computing development from Berlin, who stands for the following personal characteristic:

Open
Minded

I am always open to feedback. On the one hand, I appreciate feedback to improve my daily work. On the other hand, I do not hesitate to contribute constructive notices for improving existing processes and, of course, teamwork.

Furthermore, regular education (e.g. Reddit, conferences, leetcode, podcasts) is also part of my daily routine. I apply newly gained knowledge during implementations of PoCs (see my github page).

Team
Player

“Talent wins games, but teamwork and intelligence win championships.”
Michael Jordan

I believe in teamwork. That is not an empty phrase for me.

Master
Degree

The IT sector is complex ecosystem. A good developer must always keep up with the changing information technologies. Therefore, I decided to start my bachelor and master program in Information Systems Management at the Technical University of Berlin (exp. 2019) in order to gain more theoretical knowledge in the fields of cloud computing, databases, and microservices.

Industry
Experiences

My goal is to become an outstanding developer. Only theoretical knowledge is not enough to achieve this goal. At my current position at SAP I have been getting hands-on experiences in state-of-the-art technologies of cloud computing and machine learning.

I have also learned to deploy highly scalable products through the entire product life cycle in a distrupted team.

Technical Skills

Selection

The following section shows a selection of my technical abilities and gives you a better sense of my technical personality.

Portfolio

Selection

SAP

Machine Learning Platform

Streaming Processing Platform: 01.05.2023 - now

As a senior developer at a highly available event platform, I played a pivotal role in developing microservices that ingest and aggregate millions of data points per second. This platform was primarily utilized for providing valuable insights for an observability tool and enriching billing information for various SAP services. I spearheaded the development of several critical microservices, ensuring their high reliability and scalability to meet the demanding needs of the platform and its users.

AI Platform: 01.05.2018 - 30.04.2023

In this challenging and rewarding role, I had the opportunity to build a robust, data-intensive AI platform for the training and serving of machine learning models. As one of the first employees of this team, I took care of designing and implementing highly available and scalable microservices. These microservices were meticulously crafted to ensure smooth onboarding of new data pipelines, thereby facilitating efficient model training processes. This involved careful architecture planning, rigorous testing, and continuous optimization to meet the high standards of reliability and scalability required for this function.

I have been working on the microservices that are used to train a model and deploy the corresponding models as microservice containers on Kubernetes.
Open source projects. See this project
I have succeeded in developing and deploying a customized observability tool for observing and monitoring our landscapes.
I wrote my master thesis at SAP. The thesis deals with the improvement of the Kubernetes scheduler for batch processing (context: training of machine learning models) in a multi-tenancy environment.
Created PoC TensorFlow applications which took machine learning requirements into account.

Kubernetes: Operators, Ingress, HPA, Istio, ...
Kafka
AWS ECS, VPC, S3, EFS, ...
Java, Scala, Python, Go
Postgres / MongoDB / Redis
DataDog / Dynatrace / Prometheus
GitOps
ArgoCD / Argo Workflows
MLFlow (see here another personal project)
Docker
Terraform / Ansible
Helm
Jenkins
Git
Scrum

Watchyourfac.es

01.04.2018 - 31.07.2018

Watchyourfac.es was a student project at the Technical University of Berlin based on the field of mobile cloud computing. The goal of this project was to set up the complete architecture for a face recognition system based on machine learning where the face recognition process will take place on the edges (Raspberry Pis) rather than on a cloud server to avoid privacy issues and unnecessary traffic between the edges and the cloud system.

Implemented the model training process (inlc. set up the architecture) for the face recognition software based on AWS Batch and AWS IOT.
Set up the edge management for the backend, frontend and Raspberry Pis (via AWS IOT).
Defined a concept for immutable functional logs - This concept was based on a hash chain and asynchronous encryption.
Implemented the authentication and authorization process which was based on OAuth2 and JWT.

Serverless Framework (for basic REST API endpoints)
AWS Batch
AWS IOT
Auth0 (universal authentication & authorization platform) + JWT
Travis
JavaScript
AWS CloudFormation
Bash (Ubuntu)
Scrum
Git

Watchyourfac.es: Dashboard

Watchyourfac.es: Person of Interest Profile

Watchyourfac.es: A tagged Person of Interest

Pretrendr

15.10.2017 - 31.03.2018

Pretrendr was a student project at the Technical University of Berlin. The project was an open source project to predict technology trends out of open data sources. It is a web-based solution to extract trend data out of the worlds broadcast, print and web news and predicts the future trend potential. The primary challenge of this project was to analyse a vast amount of data in real time with Elasticsearch in combination with a caching model which was based on Redis.

Set up the architecture for the real time data analysis with Elasticsearch and AWS EMR.
Implemented the whole backend stack based on Spring Boot.
Configured the continuous deployment process with Jenkins.

Scrum
Jenkins
Elasticsearch
Rest API
AWS EC2
Databases: Redis and HyperSQL
AWS EMR in combination with Hadoop
Java
Spring Boot
Git

Pretrendr: Dashboard

Pretrendr: Custom Alerts

Deutsche Rentenversicherung

01.10.2007 - 31.03.2017

The Deutsche Rentenversicherung (German pension insurance) is responsible for the coordination of activities with the pension insurance institutes of the Member States of the European Union (EU), the European Economic Area (EEA) and Switzerland. I finished my apprenticeship at the Deutsche Rentenversicherung in 2013. After that, I had been working for the SAP developer department in full time for almost four years and as a part-time developer for another three years (during my bachelor program).

Configured a workflow from scratch which was used for the automatic communication between suppliers and the internal ERP system (e.g. for the exchange of orders, invoices, etc).
I was responsible for a major system upgrade where hundreds of users were affected (SAP-SRM upgrade from version 5 to 7).
Solved customizing and developing tasks for the SAP modules ERP-MM and SRM.

Java
REST APIs
Maven
JUnit
NGINX (loadbalancer, reverse proxy, HTTPS + TLS)
JWT authorization
ABAP
UI5
WebDynpro for ABAP
SAP Workflow Technologies
iDocs
SAP-ERP-MM and SRM

Let's Get In Touch!

Do you have any questions related to my projects, my technical background, or anything else? I am looking forward to getting in touch with you!