experial is a fast-growing AI startup on a mission to revolutionize the way companies use customer insights. Our founders are two market research PhDs and one ex-Aleph Alpha engineer.

Our mission is to generate millions of digital customer twins, that deliver instant customer insights to every business decision.

We have already built the first iteration of the product, secured initial clients, and are have raised over € 2 Mio. in venture funding to accelerate our growth.

Join us as our Senior Data Engineer and play a huge role in shaping the technological future of experial!

Tasks

As a Senior Data Engineer, you will be part of the AI Research team and responsible for the infrastructure that provisions up to 300 TeraByte of unstructured data for our LLMs.

What You'll Be Doing:

Build Petabyte-Scale Backend: Build data pipelines capable of turning Petabytes of unstructured data into hundreds of millions of digital twins and closely collaborate with the AI Research team.
Lead Technical Discussions: Actively participate in team discussions, providing expert input on technical decisions and strategic directions.
Mentor Team Members: Foster a culture of learning and growth, guiding junior developers and helping them tackle challenging projects.

Requirements

Professional Experience:

At least 8 years of professional experience in data engineering.
Preferably a Bachelor's or Master's degree in computer science, data engineering, or a related field.

Professional Experience:

At least 6 years of professional experience in data engineering.
Preferably with a background in big data companies (e.g., Palantir, DataBricks or Snowflake).

Technical Skills:

Proficient in Python, with experience in libraries and frameworks such as Pandas, PySpark, and Dask.
Experienced in building and optimizing data pipelines using tools like Apache Spark, Kafka, or similar technologies.
Strong understanding of SQL and NoSQL databases, as well as data modeling principles.
Skilled in working with large-scale data storage solutions, such as Hadoop, or similar.
Familiar with DevOps practices, including CI/CD, logging, and monitoring for data infrastructure.
Ability to design and implement machine learning data workflows, integrating with AI frameworks where necessary.

Benefits

What's in It for You:

Democratizing Customer Research: Be part of a startup that pioneers democratized customer research, leveraging your skills to bring state-of-the-art technology into the hands of our customers.
Competitive Compensation and Rewards: Enjoy a competitive salary and benefits package, reflecting your experience and the unique value you add to our team.
We're (almost) GPU Rich: Make use of up to 200k€ in cloud and GPU credits, as well as a budget for innovating our generative agent-based models.
Open Source Commitment: We plan on contributing to open-source software with our projects.
Dynamic Startup Culture: Enjoy flat hierarchies, minimal micromanagement, dedicated learning time, and weekly engineering exchanges to fuel your growth.

What are the next steps:

If you are passionate about technology, excited about AI, and ready to
make an impact in a rapidly growing startup, we want to hear from you!

Apply now with your resume, portfolio, and a brief description of your relevant experience and accomplishments.

Please include your suggested compensation in your application, as we believe
in ensuring a fair and mutually beneficial arrangement tailored to your
skills and experience.

Join experial today and help us reshape the customer insights landscape!