Senior Data Engineer

Location: Montevideo, URUGUAY, uy

Company Description

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com.

Job Description

We are looking for a Senior Data Engineer with strong experience in cloud-based MLOps to help build the technical foundation required to support a growing Machine Learning and Data Science organization.

This is a hands-on engineering role focused on building the infrastructure, pipelines, and processes needed to move machine learning solutions from development into production. The ideal candidate has strong cloud engineering fundamentals, experience working closely with Data Science teams, and a practical understanding of the machine learning lifecycle.

The primary cloud platform for the project is Google Cloud, so GCP experience is a strong plus.

Key Responsibilities

• Design, build, and maintain scalable data infrastructure supporting machine learning initiatives.
• Develop reliable data pipelines and workflows that support model development, training, deployment, and inference.
• Implement and maintain MLOps practices across the machine learning lifecycle.
• Support the deployment, monitoring, versioning, testing, and maintenance of machine learning models.
• Build automation and CI/CD processes for data and ML workflows.
• Partner closely with Data Scientists to operationalize models and move solutions into production.
• Ensure data and ML infrastructure is reliable, scalable, maintainable, and production-ready.
• Troubleshoot and resolve complex data and ML engineering challenges.
• Contribute to engineering standards, reusable patterns, and best practices for ML infrastructure.
• Help establish the technical foundation that will support future AI and agentic architecture initiatives.
• Collaborate with other Data Engineers, Data Scientists, and technical stakeholders to deliver production-ready solutions.

Qualifications

• Strong professional experience in Data Engineering.
• Hands-on experience with cloud-based MLOps.
• Experience building and maintaining production-grade data pipelines.
• Strong understanding of the machine learning lifecycle and the infrastructure required to support it.
• Experience with ML model deployment, monitoring, versioning, testing, and automation.
• Strong software engineering and programming fundamentals.
• Experience working with cloud-based data and ML environments.
• Experience collaborating closely with Data Scientists and ML teams.
• Ability to work independently on complex technical problems and deliver production-ready solutions.

Nice to Have

• Professional experience with Google Cloud Platform (GCP).
• Experience contributing to agentic architecture or AI-related infrastructure.
• Experience helping establish platforms or foundations for future AI initiatives.
• Experience working across both data engineering and machine learning engineering.

Additional Information

Our Perks and Benefits: 

📚 Learning Opportunities: 

• Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. 
• Access to AI learning paths to stay up to date with the latest technologies. 
• Study plans, courses, and additional certifications tailored to your role. 
• Access to Udemy Business, offering thousands of courses to boost your technical and soft skills. 
• English lessons to support your professional communication. 

👩‍🏫 Mentoring and Development: 

• Career development plans and mentorship programs to help shape your path. 

🎁 Celebrations & Support: 

• Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones. 
• Company-provided equipment.

⚖️ Flexible working options to help you strike the right balance.

Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.