The company
Data Mechanics is a Y Combinator startup based in
Paris, founded by Databricks and BlaBlaCar engineers passionate about
data science and automated infrastructure.
We’ve just raised a
seed round and we’re building a hassle-free managed Spark platform
backed by Kubernetes. We're on a mission to provide engineers and data
scientists with the best big data platform in the world to scale their
operations without the hassle of infrastructure management.
Spark
is the swiss-army knife of data operations, ranging from data
exploration and analytics to ML model training and ETLs. By combining
Spark with Kubernetes, we can abstract infrastructure from the user and
bring the best of modern software development to the data stack!
The opportunity
As
one of our first engineers, you’ll build with us the containerized data
platform from its inception. You’ll contribute to major product and
technical decisions that will impact the business in the long term and
set the standards for your future teammates.
You will:
-
Build a data platform running Spark on Kubernetes. Features include
autoscaling adapted to big data workloads, Spark parameters autotuning,
integrations with OS tools like Jupyter notebooks, support for
containerization of data applications
- Define the development standards and processes at Data Mechanics
- Help the recruiting effort and onboard your future teammates
- Join a young and fast-growing team building a cutting-edge product from scratch
Requirements:
- You have a BS/MS/PhD in a scientific field or equivalent experience
- You have at least 2 years’ experience contributing to a software engineering team
- You have experience programming backend services (Python or Java) for data applications
-
You have production experience running and operating Spark workloads or
internal data science platforms based on Spark or other big data engine
- You love to make complex things easy through powerful abstraction and intuitive UX
Bonus points:
- You have experience with Kubernetes
- You’ve built applications that run on AWS or GCP