Data careers

Our community of data experts and technologists think disruptively to provide pragmatic solutions for our clients' most complex challenges. We are curious minds who come together in collaborative and inclusive teams to push boundaries to make a positive impact in the world by harnessing the power of data and artificial intelligence (AI). 


We are looking for change makers, opportunity creators, status-quo shakers. If that’s you, what are you waiting for?

Current data roles

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Making an impact across data archetypes

Data engineers


are responsible for bringing our clients scalable and robust solutions related to the processes of creating pipelines, platforms, organization, governance and data quality. They have experience in cloud, on-premises technologies and migrations.

Data architects


are responsible for designing reference architectures, covering key aspects of data management, governance, domains, modeling, integration, security, compliance and more. They are responsible for the discovery, roadmap, feasibility study and recommendation of frameworks, practices and tools in the data world to better meet business objectives.

Data scientists


are responsible for identifying business opportunities and how to respond to them through the applied use of data and thus maximizing client results. They play a strategic role both from a technical and business point of view, proposing the use of advanced machine learning techniques along with algorithms and success metrics that will serve in the future to evaluate the results of production models.

ML engineers


are responsible for providing the technical components capable of enabling CD4ML principles such as experiment versioning tools, data repositories, automation mats and integration layers with production environments. They work closely with data scientists, evaluating aspects of scalability and performance for proposed data models.

Data analysts


are responsible for conducting complex analysis, proposing business indicators and generating analytic solutions to support clients in generating business value. They have experience in transforming data into insights through understanding the business and creating automated dashboards for demonstrating results and making decisions.

Life at Thoughtworks as a data professional


Learn more about life at Thoughtworks as a data professional from Clara Brünn, Data Scientist, Ina Iovitoiu, Data Scientist, Inna Zykova, Data Engineer and Javier Molina Sanchez, Lead Data Engineer. From choosing Thoughtworks to what it’s like to work here as a data professional to details of their project work and advice to those thinking of bringing their data skills to Thoughtworks – this is great insight into being a data professional at Thoughtworks.

What kind of Data and AI projects are you working on at Thoughtworks?
What advice do you have for someone exploring Data and AI at Thoughtworks?
Why did you choose Thoughtworks to grow your Data and AI career?
What is it like to work in Data and AI at Thoughtworks?

People you might work with

Katharine Jarmul

Principal data scientist, Berlin


Katharine Jarmul is a Principal Data Scientist at Thoughtworks Germany and author of the recent O'Reilly book Practical Data Privacy. Previously, she has held numerous roles at large companies and startups in the US and Germany, implementing data processing and machine learning systems with a focus on reliability, testability, privacy and security.


She is a passionate and internationally recognized data scientist, programmer, and lecturer. Katharine is also a frequent keynote speaker at international software and AI conferences.

Kelsey Bayer

Lead data engineer, Munich


Lead Engineer

Kelsey is a Lead Engineer at Thoughtworks with a background in laboratory acoustic phonetics (linguistics) and currently works as a Software Developer, Cloud Infrastructure Specialist, and Data Engineer.  She is passionate about helping clients develop products that solve real and validated business problems, building out those solutions in a pragmatic and modern way, and coaching teams on high-performance behaviours.

Talk to Kelsey about sustainable practices (both tech and non-tech) in the era of climate change or how data can contribute to this globally urgent issue.

Biplob Biswas

Lead data engineer, Munich


What I find most rewarding in my role as a data engineer is the continuous stream of challenges it presents. I derive great satisfaction from the process of identifying requirements, comprehending the problem at hand and then crafting effective solutions. While data engineering may not be perceived as the most glamorous job, its significance cannot be overstated. It serves as the foundation for any data-driven organization, enabling the creation of impactful BI reports and even powering cutting-edge technologies like Generative AI and LLMs. By ensuring the availability of high-quality data, I contribute to unlocking the full potential of data-driven initiatives.

How we help our clients

Data strategy & governance

We help our clients to get greater value from data by creating a clear roadmap that ensures trustworthiness, security and compliance, while making it effortlessly accessible and user-friendly. This way they can take control of their data landscape and empower data consumers through clear governance policies and alignment with business objectives.

Data platform modernization & Data Mesh

We support our clients to put their data into action by enabling business teams to create and consume reliable self-service data products that scale easily and support diverse analytics.


With our help they apply world-class data architecture models such as Data Mesh to bring a product mindset, modern software engineering methods, and people-centric changes to accelerate data delivery.

AI & analytics

Our data experts consult our clients in elevating their potential for extraordinary results by automating routine work and augmenting your team’s unique capabilities with people-centric, ethical artificial intelligence (AI) and analytics.

Data should challenge our assumptions and instincts from time to time. And if it doesn't there is something wrong.
Emily Gorcenski
Head of Data Europe, Thoughtworks
Data should challenge our assumptions and instincts from time to time. And if it doesn't there is something wrong.
Emily Gorcenski
Head of Data Europe, Thoughtworks

Take the next step in your data career journey

Preventing disaster with data testing: Real-life examples and best practices
Anna Lagutina


As data-driven applications become increasingly prevalent, it's important to ensure they meet software best practices and standards. With incorrect analysis, we can fail to understand data, accidentally introduce bugs, have mismatching test sets and real-life data, misinterpret our data analysis and who knows what else can go wrong?

Unlocking value from Data and AI at scale
Danilo Sato and Kiran Prakash


In this webinar, Thoughtworks' experts discuss the benefits of using the Data Mesh approach and the disadvantages of a centralized data management system, drawing on real life data projects.

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