Job description
About Unbabel
Unbabel's language operations platform blends advanced artificial intelligence with human editors to deliver fast, efficient, and high-quality translations that get smarter over time. Unbabel integrates seamlessly across multiple channels, enabling enterprises to deliver consistent multilingual support from within their existing workflows.
Today, Unbabel operates as part of as part of TransPerfect, a global leader in language and technology solutions.
What’s the opportunity about?
Unbabel is looking for a curious and motivated Data Engineering Intern to join our Data Platform team. As we deliver seamless, scalable translation solutions for enterprise partners worldwide, you'll gain hands-on experience designing and building the data platform that powers Unbabel's core products and analytics. This is a unique opportunity to work with large-scale, real-world language and translation data in a production environment — learning how it's ingested, processed, stored, and analyzed at scale. You'll be part of a friendly, international, and diverse engineering team committed to your growth, with supportive mentors to guide you through modern data engineering workflows and cloud data platforms. Want exposure to real-world data pipelines, distributed systems, and cloud infrastructure? Here's where you can build those skills while making a meaningful impact.
What you’ll get out of it:
Hands-on experience with production-grade, large-scale data in a real-world environment.
Mentorship and exposure to modern data engineering practices and cloud platforms
The chance to contribute ideas and make a tangible impact on products used by global enterprises
A collaborative, diverse team culture where your growth and success actually matter
What you’ll work on:
Design, build, and maintain batch and streaming ETL pipelines in a production environment
Develop and test high-quality code for ETL pipelines (Python and Spark)
Work with structured and unstructured data from multiple sources (mainly MongoDB and Postgres)
Apply data warehousing techniques to a modern cloud-based stack (Databricks)
Help monitor, test, and validate data to maintain high standards of data quality
Collaborate with data engineers, data analysts and other technical teams to translate business requirements into data solutions
Participate in code reviews and team discussions, picking up best practices in code quality and architecture
Troubleshoot and debug data systems, and document your work to improve team processes
Job requirements
What we're looking for in you:
Bachelor or Masters degree in Computer Science, Data Engineering, Software Engineering, or a related field — ongoing Masters is also welcome
Programming skills — preferably Python or a similar language
Comfortable with SQL and structured databases
Interest in data engineering, databases, cloud services and big data
Curiosity, willingness to learn, and eagerness to ask questions and seek feedback
Ability to communicate in English and collaborate effectively in a team
Nice to have:
Familiarity with cloud platforms (e.g. AWS, GCP, Azure)
Previous involvement in team projects — professional, university, personal, or open-source
