Berlin based - m/f/d - full-time

What we do at Plato

Plato is building the digital backbone of the global trade economy. Starting with the $53T wholesale industry, we empower the modern wholesaler to connect their people and data in a single analytics and workflow hub. By leveraging data science and AI we automate workflows and combat labor shortage making SMB wholesalers competitive with large corporations.

🎯 Why we do what we do

The future of wholesale is data-driven. Unlike popular opinion, Industrial SMEs are ready to make the step to become more proactive in their processes but lack the technology to steer them to success. Our founders come from a wholesale family and gathered a rock star team of ex-Big Tech, VC and top tier consulting companies to reshape the operations of this $48tn industry. Our initial product leverages cutting-edge data science to provide customized demand forecasts and product recommendations combined with intelligent workflow automation.

We are about to create category-defining software. Our primary customers are C-suite executives within large-scale wholesale and distribution businesses. We are committed to helping them enhance their decision-making processes and optimize their operations through the smart use of their data - bringing their operations into the 21st century! But don’t just hear it from us! We are supported by a list of top-tier EU & US VCs, advisors, and angels providing insights from some of the best SME tech companies such as Miro, Celonis, Personio, Workday, Forto and Microsoft.

Short Description

As a founding team member, you'll lead development of our real-time data platform, data warehouse, and infrastructure for our suite of data products. You'll work closely with data science, product, design, and engineering teams to build the data foundation that powers customer-facing analytics and ML models.

Responsibilities

Carry out data modeling that powers real-time customer-facing analytics and data products
Design flexible schemas that store data from many different sources
Develop and maintain data pipelines for machine learning algorithms and real-time dashboards
Partner with data consumers across Plato to understand consumption patterns and design intuitive data models
Write and deploy high-performance real-time transformations within our data warehouse
Own and configure our data platform (Databricks)

🚀 What you’d be working on

Carry out data modeling that powers real-time customer facing analytics and a portfolio of data products that are consumed in our app
Design flexible schemas that store data from many different sources
Develop and maintain data pipelines for machine learning algorithms and real-time dashboards
Partner with data consumers across Plato to understand consumption patterns and design intuitive data models
Write and deploy high-performance real-time transformations within our data warehouse
Own and configure our data platform (Databricks)
Collaborate with our product and engineering teams to build a data product that our end-users love

🏅 What you bring along

3+ years of experience in data engineering; high-growth tech company experience is a plus
You have experience building ETLs/ELTs, ideally in PySpark and Airflow.
Experience in working with SQL, data warehouses (e.g. Databricks or Snowflake) and data transformation workflows (e.g. dbt)
You have interest in data engineering practices and product knowledge, specifically in how to leverage the power of analytics to power customer facing applications
You have a solid understanding of Software Engineering practices and Data Engineering principles. MLOps knowledge would be appreciated.
Mentality: An experimental mindset with a launch fast and iterate mentality. A strong statistics/mathematics background is a plus

🛠️ The tools you will be using

Python
Spark/PySpark
Data Modeling
SQL
Databricks (Delta Lake)
DBT
AWS

🗒 Hiring Process

Step 1: Intro call (20 min.) - Oliver

Intro call with one of the founders to get to know each other and introduce Plato.

Step 2: System design - Bob

Technical interview with Bob, Data Engineering Lead

Step 3: Technical fit

One technical challenge (take-home exercise),
followed by a call in which you present and elaborate on your take-home exercise.

Step 4: Meet the founders

Meet the other co-founders

Step 5: Reference checks

Before sending the offer, we ask you to provide 2-3 contacts for us to do some reference checks.

Step 6: Offer

Congratulations! We are convinced by your skills and personality and see a great fit! You will get an offer from us including an appropriate share package.

We are moving fast, and we also want to grow our team fast – that is why we are trying to conclude the whole process within a short time (2-4 weeks).

🖌️ Our way of working

Office: We work from our beautiful and centrally-located Berlin office
- We believe working on-site is crucial in our stage to foster ideas and communication
- We are, however, open to remote work once a year to escape the Berlin winter
Team: Regular team events and lunches
Tech: Top of the range tech setup
Package: Competitive comp and meaningful equity in rapidly growing startup

🦄 You should join Plato if,

you’d like to be part of a rocket ship backed by top-tier investors from day one,
digitize an old economy with cutting-edge AI technology,
while enjoying the adventurous and demanding road of venture building,
in a team of motivated A-players who push hard to make this a reality

We are excited to hear from you!

Oliver, Aram and Bob

Compensation: €70K – €120K • Offers Equity

• €70K – €120K • Offers Equity