Senior Data Engineer
Welo Data (Welocalize) · Mexico City, Mexico · Remote
- Source
- welo-data
About this role
About Welo Global Welo Global is a leader in multilingual AI, technology, and content solutions serving over 2,000 clients in 300 languages. The company combines globally scaled multilingual infrastructure, including a network of over 500,000 linguists and domain experts, with advanced NLP, computational linguistics, and best-in-class compliance backed by seven ISO certifications. Welo Global’s five brands—Welocalize (multilingual content and localization services for global enterprises), Park IP (intellectual property and patent translation services for law firms and corporate legal teams), Welo Life Sciences (regulated language and compliance-aligned content solutions for pharmaceutical, biotech, and medical device organizations), Adapt (multilingual performance-led digital marketing agency), and Welo Data (multilingual data generation, evaluation, and human data infrastructure for AI systems)—serve distinct customer segments with purpose-built expertise, fit-for-purpose solutions, and supporting technology. weloglobal.com The Senior AI/ML Data Engineer is a hands-on technical contributor responsible for designing, building, and maintaining the data infrastructure that powers AI/ML product features across the organization. This includes building ETL pipelines between diverse data sources and destinations, architecting new solutions to support production-level APIs, syncing application data into analytics-ready warehouses, and tackling ad hoc data challenges that don't fit neatly into existing patterns. The scope of work varies from standing up repeatable sync jobs to researching and prototyping new approaches for problems the team hasn't solved before. The ideal candidate is someone who thrives in a fast-moving product engineering environment, can navigate ambiguity in requirements, take ownership of problems from investigation through production deployment, and maintain a high standard of documentation and data quality. They should be equally comfortable maintaining established pipelines and independently researching new tools or architectures.
Skills & domains
- ai-training
- linguistics
- expert