Data Engineering Manager

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

We are seeking a to contribute to our next level of growth and expansion.

Job Description
We're looking for a skilled
Data Engineer Manager
with strong experience in
Snowflake
and
Python
to help design and implement an end-to-end data architecture for a leading enterprise client's
marketing team
.

This role is part of a strategic initiative to enable robust analytics and insight generation for marketing and martech use cases.

In this role, you'll work closely with both Blend's internal teams and client stakeholders to
build and optimize data pipelines
, support data modeling efforts, and ensure reliable data flows for reporting, analytics, and operational workflows.

This position is ideal for engineers with a strong data foundation who are looking to apply their skills in
analytics, BI, and marketing tech environments
, while gaining exposure to modern data tools and scalable architectures.

You Will

• Design and implement an end-to-end data solution architecture tailored to marketing analytics and martech needs.
  
  
• Build, maintain, and optimize data pipelines and transformations using Python and Snowflake.
  
  
• Support analytics and BI teams by ensuring clean, reliable, and well-modeled data.
  
  
• Leverage tools like Fivetran and dbt (if available) to orchestrate ELT processes.
  
  
• Collaborate with cross-functional teams to align on business goals and technical requirements.
  
  
• Contribute to documentation and continuously improve engineering and data quality processes.
  
  

Qualifications
Qualifications

• 6+ years of experience in data engineering.
  
  
• Proficiency in Python for data workflows and pipeline development.
  
  
• Strong experience in MLOps, including automation of machine learning pipelines, model deployment, and production monitoring.
  
  
• Solid experience working with Snowflake or similar cloud data platforms.
  
  
• Experience (or familiarity) with marketing data, martech tools, or marketing analytics use cases.
  
  
• Understanding of analytics/BI environments and how data supports decision-making.
  
  
• Exposure to tools like dbt and Fivetran is a plus.
  
  
• Familiarity with cloud platforms such as AWS, GCP, or Azure.
  
  
• Strong communication and documentation skills.
  
  
• Ability to thrive in collaborative, client-facing environments.
  
  

Preferred Qualifications

• Hands-on experience with dbt, Fivetran, or similar modern data stack tools.
  
  
• Familiarity with CI/CD pipelines or infrastructure-as-code practices.
  
  
• Experience in client services, consultancy, or agency settings.
  
  

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

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.