Data Engineer

We’re looking for a skilled Data Engineer with strong experience in Python, Terraform, and AWS to help design and implement scalable data architectures for AI and analytics applications. This role is part of a strategic initiative to enable robust data pipelines, infrastructure automation, and cloud-based analytics capabilities for enterprise clients.

In this role, you’ll work closely with Blend’s internal teams and client stakeholders to build and optimize ETL/ELT workflows, develop backend services, and ensure data quality, governance, and security across all environments.

This position is ideal for engineers with a strong data foundation who are looking to apply their skills in modern cloud ecosystems, big data processing, and infrastructure as code while gaining exposure to tools like Databricks and Snowflake.

You will:

• 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 data processing systems.

• Develop and maintain Python-based backend services to support data infrastructure.

• 4+ years of experience in data engineering.

• Strong proficiency in Python for building data-driven solutions.

• Hands-on experience with Terraform for provisioning and managing cloud infrastructure.

• Strong experience with Infrastructure as Code (IaC) principles and CI/CD pipelines (Terraform + GitHub Actions).

• Experience working in AWS cloud environments (infrastructure and services oriented to data solutions).

• Hands-on experience with data processing using Pandas or PySpark.

• Deep understanding of cloud-based data platforms such as Databricks and Snowflake (Databricks preferred).

• Strong communication and documentation skills.

• Ability to thrive in collaborative, client-facing environments.

Preferred Qualifications

• SQL experience.

• Hands-on work with Databricks.

• Familiarity with modern CI/CD practices and tooling.

• Experience in consultancy or client-service environments.

Language Requirements
You must have excellent written and verbal English communication skills.

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.