What We are Doing 

• Kaizo is leveraging gamification and machine learning to make the daily work experience for customer support agents more engaging, fun and productive.
• We run a microservice-based stream processing platform which processes 200+ million events every day using Akka Streams and Kafka.
• Those services are deployed to Kubernetes on Google Cloud and feed data into Elasticsearch and Mongodb.
• Our systems are designed to be reactive, e.g. responsive, resilient, elastic, and message-driven.
• We are building a realtime Machine Learning engine to continuously adjust the gamification parameters that keep our users motivated and productive.
• We are always scaling up to handle more data with lower latencies.

Why this role? 

• Make a massive impact on the company. We are growing fast, and over the next year, we will go much, much bigger. As a data engineer, you will have an awesome opportunity and a challenge to help us scale to thousands of clients and millions of end-users.

• Broaden your skills. Being a part of an early-stage startup, we sometimes need to wear many hats. You’ll get experience with scaling a startup and building a product.
• Learn fast. Kaizo is developing at an extremely high speed and you will be able to take on new challenges and learn.
• Join us at a magical time. We’ve achieved a lot with a small team, which allows you to experiment and be creative.

Your job will be

We are looking for a data engineer that will help us build and maintain scalable data pipelines, code intensive data processes, take machine learning models from notebooks, train them on scale, build endpoints that will serve thousands of predictions in real time.

You will also be focused on:

• Building efficient processes that implement the full data science cycle

• Processing, cleaning, and aggregating data used for analysis
• Improving and extending the features used by our existing systems
• Performing ad-hoc analysis and presenting results in a clear manner
• Creating automated systems and constantly trackig its performance
• Building endpoints that will serve thousands of predictions in real time
• Collaborating with other teams within the company to improve decision making and drive product development
• Communicating results and ideas to key decision makers
• Experimenting with different tools and technologies, and evaluate new data science approaches for the business 

What you bring to the table:

• 2+ years industry experience in data engineering.

• Experience with Kafka and Spark streaming is a must.
• Good scripting and programming skills using Python.
• Experience with Scala is a huge plus
• Experience building ETL tools.
• Experience with an MLops tool like kubeflow, Argo, MLflow, etc.
• Experience in using the following tools and technologies is a plus: Google Cloud Platform, Github, Docker, Kubernetes, MongoDB, Elasticsearch
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Understanding of data science & machine learning techniques and algorithms, such as clustering, supervised learning, and neural networks is a plus.
• Data-oriented personality
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.

Being part of an early stage startup we sometimes need you to wear multiple hats just to keep things going, hence being a team player is a must have.

What We Bring to the Table

You will work with some of the best global talent to build a tool used by great companies like Booking.com, Marleyspoon, Footlocker, Soundcloud, Tripaneer or WeTransfer. You will be part of a team of diverse and passionate people with a culture that empowers great work.

We do everything to make sure you feel motivated and supported by offering:

• Teamwork & fun perks when full remote work is required (weekly team games & drinks, morning coffee chats and more)

• Investment into your personal development using our network of internal and external mentors
• New laptop & tools
• Free lunch (even while working from home)
• Flexible working hours and unlimited holiday policy
• Workations (2019: Tuscany, 2020: Zoom 😢, 2021: ???)