Senior Data Engineer

Summary

Join Montevideo Labs | A Blend Company, a thriving tech company with over 10 years of experience in big data, to design, build, and optimize scalable data pipelines for AI and analytics solutions. As a Senior Data Engineer, you will work on the architecture and deployment of data infrastructure, ensuring efficiency, reliability, and security. You will collaborate with cross-functional teams and lead troubleshooting efforts. The position offers 100% remote work if you reside in LATAM or the option to work in the Montevideo, Uruguay office. The company values professional development and offers various perks and benefits.

Requirements

• Strong proficiency in SQL for data processing and transformation
• Strong knowledge of object-oriented programming in at least one language (Python, Scala, or Java)
• Hands-on experience deploying and managing large-scale data pipelines in production environments
• Expertise in workflow orchestration tools like Apache Airflow, Dataplane, or equivalent
• Deep understanding of cloud-based data platforms such as Databricks and Snowflake (Databricks preferred)
• Knowledge of CI/CD pipelines and infrastructure as code for data workflows
• Familiarity with cloud environments (AWS preferred, Azure, or GCP) and cloud-native data processing
• Expertise in Spark, PySpark, and Spark SQL, with a solid understanding of distributed computing frameworks
• Proven ability to lead projects and mentor junior engineers in a fast-paced, collaborative environment
• Excellent written and verbal English for clear and effective communication
• 4+ years of experience working as a Data Engineer or related positions

Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines for AI and analytics applications
• Optimize data architectures and storage solutions using Databricks, Snowflake, and cloud-based platforms
• Develop big data processing jobs using PySpark, Spark SQL, and distributed computing frameworks
• Ensure data quality, governance, and security best practices across all environments
• Implement CI/CD workflows for automated deployment and infrastructure as code (IaC)
• Collaborate with cross-functional teams (data scientists, software engineers, analysts) to build end-to-end data solutions
• Lead troubleshooting and performance tuning efforts for high-volume data processing systems
• Develop and maintain Python-based backend services to support data infrastructure
• Implement Apache Airflow, Dataplane, or similar orchestration tools to automate and monitor workflows

Benefits

• 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
• English lessons to support your professional communication
• Career development plans and mentorship programs to help shape your path
• Anniversary and birthday gifts
• Company-provided equipment for remote work