Senior Data Engineer
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
We’re looking for a skilled Senior Data Engineer with strong experience in Snowflake-based data platforms, AWS, and modern data ingestion frameworks to help design and implement scalable ingestion and validation architectures for a leading enterprise client. This role is part of a strategic initiative to enable high-quality, governed, and reliable data pipelines that support analytics and business-critical workflows.
In this role, you’ll work closely with both Blend’s internal teams and client stakeholders to build robust ingestion pipelines, implement data quality and validation frameworks, and ensure trusted data flows across the organization.
This position is ideal for engineers with a strong data engineering foundation who are passionate about data quality, automation, and governance in modern cloud data environments.
You will:
Design and implement data ingestion architectures on Snowflake.
Design, develop, and implement scalable data pipelines and architectures on AWS.
Build and maintain ingestion pipelines integrating multiple data sources.
Define and implement data quality checks, validation schemas, and testing frameworks.
Establish data governance components including glossary definitions and data stewardship patterns.
Develop the Streamlit-based ingestion validation UI and its backend logic.
Collaborate with cross-functional teams to align technical solutions with business requirements.
Contribute to documentation and continuous improvement of data reliability and quality processes.
- 3+ years of experience in data engineering
- Strong hands-on experience in Snowflake-based ETL pipelines (Must)
- Hands-on experience in Snowflake Cortex (Plus)
- Hands-on experience building and maintaining data pipelines in AWS (Plus)
- Experience building CI/CD pipelines for data workflows (Plus)
- Solid understanding of data quality, validation frameworks, and governance practices
- Experience with AWS - Snowflake data sharing over Iceberg tables (Plus)
- Strong communication skills, with the ability to work independently and collaborate across technical and business teams
- Experience with AWS ecosystem tools such as Glue, Athena, EMR, S3/Lambda, and infrastructure-as-code tools like CloudFormation, Terraform, or CDK, as well as dbt (Plus)
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.
Travel opportunities to attend industry conferences and meet clients.
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.