Florian Pfisterer, Developer in Munich, Bavaria, Germany
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Florian Pfisterer

Verified Expert  in Engineering

Back-end Developer

Location
Munich, Bavaria, Germany
Toptal Member Since
July 12, 2021

Florian has over five years of experience in back-end software engineering. He is skilled in Java, AWS, Node.js, SQL, and Python, with a focus on scalable cloud infrastructure, fast algorithms, and clean API design. In addition to a recent SE internship at a big tech company, in Florian's previous job, he led a team of five remote contractors and in-house developers. His industry experience is backed by a bachelor's degree in computer science from KIT and CMU.

Portfolio

HubSpot
Java, Amazon Simple Queue Service (SQS), Apache Kafka, HBase...
PLAYSPORTS GmbH
Python, Node.js, TypeScript, SQL, Redis, Redis Queue, AWS Lambda, React...
Carnegie Mellon University
Python, Research, Machine Learning, Generative Pre-trained Transformers (GPT)...

Experience

Availability

Part-time

Preferred Environment

MacOS, GitHub, Amazon Web Services (AWS), TypeScript, Node.js, Python, SQL, Linux, Java

The most amazing...

...thing I've worked on is the core infrastructure of HubSpot's extremely scalable sending pipeline and webhook processing system.

Work Experience

Software Engineering Intern

2022 - 2022
HubSpot
  • Developed a robust acceptance test infrastructure that monitors the correct functioning of core business priorities.
  • Worked on a highly scalable microservice architecture using Kafka, Apache HBase, and AWS SQS.
  • Designed and built a Cloudflare edge worker to correctly route incoming requests.
Technologies: Java, Amazon Simple Queue Service (SQS), Apache Kafka, HBase, Distributed Systems, Monitoring, Metrics, Testing, Microservices, Microservices Architecture, Back-end, Twilio API, Twilio, JSON, Webhooks

Lead Software Engineer

2019 - 2021
PLAYSPORTS GmbH
  • Architected a scalable cloud architecture with multiple databases on AWS, including CI/CD pipelines, autoscaling, a load balancer, and AWS Lambda.
  • Developed a clearly documented Node.js, TypeScript, and Express.js REST API with cron jobs, job queues, Redis caches, WebSockets, and complex SQL queries.
  • Created a unit and end-to-end test suite with Mocha to automatically test all critical endpoints and features.
  • Built two microservices in Python for machine learning and natural language processing tasks that provide recommendations, automatic tagging, and matching.
  • Integrated with diverse third-party APIs, including Stripe, Google Maps, Google BigQuery, Firebase Analytics, and Quaderno.
  • Constructed a resilient payment system for subscriptions, deferred one-time payments, coupons, and invoicing based on Stripe.
  • Led the technical aspects in a sports app startup, built the tech culture and established software engineering standards, onboarded seven new developers, and performed code reviews and sprint planning.
  • Implemented the parts, maintained, and conducted code reviews for two React web apps and admin dashboards.
Technologies: Python, Node.js, TypeScript, SQL, Redis, Redis Queue, AWS Lambda, React, Testing, Stripe, JavaScript, REST APIs, Architecture, Databases, DevOps, Mathematics, API Integration, Scripting, Amazon Web Services (AWS), Amazon EC2, NGINX, CI/CD Pipelines, Microservices, RESTful Microservices, Microservices Architecture, Amazon S3 (AWS S3), Back-end, Exports, Amazon DynamoDB, JSON, Webhooks

Visiting Research Scholar

2019 - 2019
Carnegie Mellon University
  • Conducted natural language processing research on the semantic parsing of instructional texts, such as cooking recipes and DIY guides, and based my bachelor's thesis on the research.
  • Developed automation tools, parsers, and converters in Python, some of which can be found on my GitHub profile.
  • Ran machine learning experiments and training on remote Linux servers.
Technologies: Python, Research, Machine Learning, Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Linux, PyCharm, Scripting, API Integration, JSON

Assistant Researcher

2018 - 2019
Karlsruhe Institute of Technology
  • Developed a 2D-LSTM for sequence-to-sequence learning in PyTorch from scratch as a research project (see GitHub).
  • Conducted neural machine translation experiments and training on remote Linux servers with GPUs.
  • Created a detailed unit test suite for the PyTorch 2D-LSTM model.
  • Wrote a detailed report about the research project.
Technologies: Python, Machine Learning, Linux, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), GPT

Co-founder and Developer

2017 - 2019
Courtastic
  • Developed a REST API back-end for a court booking application on DigitalOcean Linux servers, accessing a MySQL database.
  • Designed and developed a native iOS app with over 2,500 users in two countries. Built with Swift with a REST client, custom views, and authentication.
  • Founded the company, which PLAYSPORTS GmbH acquired in January 2019.
  • Maintained a React web app and a Bootstrap HTML and CSS landing page.
  • Marketed and sold the product used by 22 tennis clubs in Germany and Austria.
Technologies: DigitalOcean, SQL, Swift, iOS, Linux, REST APIs, NGINX, React, REST, HTML, Back-end, JSON, Webhooks

PLAYSPORTS Back End

An all-in-one mobile app that provides access to a multisport community and connects players, sports grounds, and events to a global network, using intelligent algorithms. As the lead back-end engineer, I led the technical team of five developers and built a scalable server architecture on AWS. The back end provided a clearly documented REST API, WebSockets, Redis caches and queues, payment processing via Stripe, and integrated with several other third-party APIs.

Automatic Tagging Microservice

A microservice for automatically tagging documents, managing synonym reconciliation, and incrementally building a set of tags. I developed it in Python and hosted it on AWS with a fully automated CI/CD pipeline. It exposes a REST API and manages a local SQLite database that holds information about all previously encountered documents and tags, which is used to improve tagging capabilities over time.

Graph-based Recommendation System

A recommender system that uses a graph stored in Redis to make user-user recommendations within the PLAYSPORTS app. After extracting candidates from the graph, it ranks them using cross-feature vectors for each user. I developed the system as a microservice in Python, hosted on AWS, with fully automated CI/CD. It uses RedisGraph, Celery, and NumPy.

Personal Blog About AWS and Server Architecture

https://pfisterer.dev
My personal website where I occasionally write articles about interesting technical challenges I have encountered, explaining how I approached and solved the problem. My favorite article is about a map caching solution that yielded a 50x speedup in request duration. The blog was built using Next.js and React and deployed on Netlify.

Containerized Microservices Architecture on Azure

https://electrojoule.ch
I worked as the lead developer on a containerized microservices architecture for a renewable energy IoT application consisting of eight services on Azure. To ensure it stays available, I've added a complete monitoring solution using tools such as StatsD and Netdata. In addition, I've developed a custom end-to-end test system that tests core business functionality in set intervals and sends alerts if something does not work. This has increased the availability from around 95% to over 99.9%.

Languages

TypeScript, Python, SQL, JavaScript, Java, Swift, HTML

Libraries/APIs

Node.js, Stripe, REST APIs, Redis Queue, React, Twilio API, NumPy

Paradigms

REST, API Architecture, Testing, DevOps, Microservices Architecture, Mobile App Design, Microservices

Platforms

MacOS, AWS Lambda, Amazon Web Services (AWS), Amazon EC2, Visual Studio Code (VS Code), Linux, Twilio, DigitalOcean, iOS, Netlify, Apache Kafka, Azure, Docker

Storage

Databases, JSON, Redis, MongoDB, MySQL, Amazon S3 (AWS S3), Amazon DynamoDB, Redis Cache, SQLite, HBase

Other

Algorithms, Software Engineering, APIs, JSON REST APIs, Back-end, Webhooks, Mathematics, Machine Learning, CI/CD Pipelines, Message Queues, Architecture, Cloud, Lambda Functions, Scripting, API Integration, RESTful Microservices, Web Security, Monitoring, Exports, Decision Trees, Research, Natural Language Processing (NLP), Mobile App Development, Back-end Development, Team Management, Scalable Architecture, WebSockets, Industrial Internet of Things (IIoT), Distributed Systems, Metrics, Netdata, Cloud Infrastructure, Containers, GPT, Generative Pre-trained Transformers (GPT)

Tools

GitHub, PyCharm, NGINX, Celery, Azure IoT Hub, Amazon Simple Queue Service (SQS)

Frameworks

Next.js, Stripes

2021 - 2022

Master's Degree in Computer Science

Technical University Munich - Munich, Germany

2016 - 2019

Bachelor's Degree in Computer Science

Karlsruhe Institute of Technology - Karlsruhe, Germany

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