Data careers

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.

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. 

Lead data scientist, Brazil

I was still in college when I joined Thoughtworks in 2018 as a junior consultant developer. Thoughtworks was a dream for me. Thoughtworks University (our internal graduate program) opened doors to show me the potential of doing things I didn't know I was capable of. After this amazing period, I also had the opportunity to go to Thoughtworks Data University in India, meet incredible people from all over the world and gain precious knowledge about data engineering. 

I changed my role to data engineer and started to work with an international client improving a data flow that consumed millions of events a day. However, I knew my passion was data science. I wanted to work with data since I took AI classes in 2016. In 2022, I started an MBA in data science at University of São Paulo, sponsored by Thoughtworks. And in 2023 I earned my MBA degree and had opportunities to officially work as a data scientist.

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.