Job description
Company Description
Are you looking for an opportunity to jump-start your career in a thriving tech industry? Join us at Montevideo Labs | A Blend Company to grow our business and execute our mission to help organizations leverage data and technology to make better decisions. With over 10 years of experience in the field of big data, top US customers such as Mastercard, Tripadvisor, and Roku choose us to develop innovative products.
What is this position about?
As a Senior Data Engineer, you will be responsible for designing, building, and optimizing scalable data pipelines that power AI and analytics solutions for our clients. You will work on the architecture and deployment of data infrastructure, ensuring efficiency, reliability, and security across large-scale datasets, as well as being hands in the development process.
You may work 100% remotely if you are currently living in LATAM, or you can always join us at the office in Montevideo, Uruguay!
Job Description
- 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.
Qualifications
- 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.
What about languages?
Excellent written and verbal English for clear and effective communication is a must!
How much experience must I have?
We’re looking for someone with 4+ years of experience working as a Data Engineer or related positions.
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.
- English lessons to support your professional communication.
👩🏫 Mentoring and Development:
- Career development plans and mentorship programs to help shape your path.
🎁 Celebrations & Support:
- Anniversary and birthday gifts.
- Company-provided equipment for remote work.
🌎 Regional Flexibility:
- Other benefits may vary according to your location in LATAM.
