Our community of Data Experts 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?
Making an impact across data careers
is responsible for conducting complex analysis, proposing business indicators and generating analytic solutions to support clients in generating business value.
is responsible for bringing our clients scalable and robust solutions related to the processes of creating pipelines, platforms, organization, governance and data quality.
is responsible for designing reference architectures, covering key aspects of data management, governance, domains, modeling, integration, security, compliance and more.
is responsible for identifying business opportunities and how to respond to them through the applied use of data and thus maximizing client results.
is 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.
Thoughtworks stands out for its collaborative and people-centric culture, where the emphasis on robust software engineering practices complements the focus on data engineering. The company excels in bridging the gap between data expertise and solid software engineering, making it a unique and fulfilling workplace.
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.
How we help our clients
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.
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.
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.
Our people
Senior Data Scientist, Finland
"My interest in data science started with my interest in mathematics. At the end of my physics studies at University of Jyväskylä I realized that I wanted to pursue my career closer to people and real-life business problems rather than academia. This sparked my interest to study data science and machine learning on my own time and through courses provided by the university, and here we are. Before joining Thoughtworks I was a data scientist at a product and gaming company, Rovio, where I mostly focused on data modeling."
Data Engineer, United States
"I joined Thoughtworks as a Software Developer after graduating with a Math and Physics degree. I knew very quickly that I wanted to use all of the skills I had gained, which made the pivot to data engineering very natural. I went through Thoughtworks' data residency program and worked on two data projects right away, which solidified my interest in data.
It was rewarding to participate on my first project not just because it was intellectually stimulating but also because it was tech for good. I'm happy to say I am a Data Engineer here!"
Lead Data Engineer, Germany
"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."
Recommended content
Mike Mason and Birgitta Böckeler
In recent months, there's been a lot of talk in the industry around issues like whether AI might boost developer productivity and if it can be used for pair programming, but in this episode of the Technology Podcast we try to get beneath the hype to explore the reality of generative AI and software development — how is it actually being used today? What works? And what doesn't?
Stephanie Wang
Ever wonder how XR worlds are built? Come see how one beginner with no formal XR background created her own AR app and VR world. In less than 15 minutes you'll learn some tips and tricks and see what’s behind the scenes in XR world building.