Want a data team without the cost
of a fulltime hire?

Data as a subscription service

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Want a data team without the cost
of a fulltime hire?

Want a data team without the cost of a fulltime hire?

Data as a subscription service

Our Approach

At DataVibes, our mission is to make data work for you, without the complexities of traditional full-time hires. Our approach combines the incredible developments in technology, such as cloud computing, the modern data stack and generative AI, with an unwavering commitment to what we like to call the data fundamentals.

We offer:

1. Diverse Data Expertise

Recognising your range of data needs, we provide specialisation across the entire data value chain. Whether you need occasional support or ongoing assistance, we can build or maintain your machine learning models, configure your product analytics tools, develop your business dashboards, manage your data architecture, choose your tech stack and much, much more.

2. Data Quality Hyperfocus

We prioritise getting our data engineering basics right.

This means creating single sources of truth for datasets and metrics, prioritising structured data modelling as well as implementing testing and monitoring strategies.

A solid foundation is the key to unlocking your data's full potential.

3. Simplified Onboarding:

We believe accessing data services and products should be straightforward. Bid farewell to the complications of building, training, and managing full-time data teams. We offer transparent flat day rates and retainers, ensuring a hassle-free purchasing experience.

Take your data from 0 to 1
We will build and manage your data operations from the ground up, including....
Data Science
...and more
get started
First two options don't work?
We are also available on a individual freelancing or contract basis with custom terms.
get started

Schedule your free consultation now

The tech stack we love

We have worked with many tools in our time but there is a set that we like to work with more than most, due to their integrations with each other, ease of use and fantastic features for delivering data value. This means we can get things up more quickly, cheaply and with better results and then pass the benefits on to you.

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Who we are

Under industry titles like Data Scientist, Business Intelligence Analyst and Data Engineer we have all spent most of our careers working across the data stack. We like using the title “full-stack” data scientist to describe ourselves.

Thomas Zenkner

People and process focused
Barcelona, Spain
Thomas has spent his career solving problems in a mix of startups and corporates across web3, grocery delivery, recruitment, public sector and consulting organisations. He has spearheaded several greenfield data projects at startups and feels most fulfilled when he has the opportunity to build things from scratch.

Outside the world of data, Thomas is deeply passionate about football and learning Spanish.

He has an MSc in Business Analytics from University College London.

Moritz Stoll

A master of data engineering
Erfurt, Germany
Moritz loves nothing more than building unbreakable data pipelines, and loves using BigQuery, Airbyte and Airflow to get the job done. During his free time, he thinks a lot about how to deploy the perfect tech stack.

With a BE in Practical Computing from the Duale Hochschule Gera-Eisenach, he brings a wealth of experience with the messiest of datasets from his career spent in freelancing and contracting.

He has two dogs and is a huge Star Wars fan.

Gabriel Zenkner

Our best "quant"
London, United Kingdom
Gabriel holds an MSc in Advanced Mechanical Engineering from Imperial College London and had his thesis on time-series weather prediction published. He has worked in both startups and multinational corporations like GE Healthcare developing high impact scientific and commercial products.

His favorite work involves using Python, SQL and Tableau to conduct analyses that deliver real value to stakeholders.

His hobbies include running, boxing, music and travel.

Sold? Let's book that call in!