Senior Data Engineer

About the company

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 are seeking a Senior Data Engineer to contribute to our next level of growth and expansion.

Full job description

What is this position about?

We are looking for a Senior Data Engineer to contribute to the design and implementation of scalable, domain-oriented data solutions for a high-impact enterprise initiative. You will work within a specific data domain — such as Ingestion, Customer Data, Enrichment, or Marketing Signals — ensuring high-quality, reliable data pipelines that power analytics and business-critical workflows. You may work 100% remotely from anywhere in Mexico!

• Contribute to the design and development of scalable data pipelines on AWS (Glue, S3, Athena, Step Functions).
• Build and optimize batch and streaming ingestion pipelines, including CDC-based architectures.
• Support the design and implementation of data models aligned with business and analytics needs.
• Ensure data quality, reliability, and performance across pipelines and datasets.
• Collaborate with cross-functional teams to align technical solutions with business requirements.
• Apply best practices in data engineering, including modular design, reusability, and governance.
• Leverage AI-assisted development tools to improve productivity and code quality.
• Proactively identify risks, bottlenecks, and optimization opportunities across data workflows.

Qualifications and requirements

What are we looking for?

• 4+ years of experience in Data Engineering
• 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 (Must)
• Strong hands-on experience with Python and PySpark (Must)
• hands-on experience in Snowflake-based ETL pipelines (Plus)
• Deep understanding of data pipeline architecture and design patterns
• Experience implementing and scaling CDC (Change Data Capture) patterns
• Strong experience in data modeling for analytics and reporting
• Experience leading initiatives or teams in data engineering environments
• Familiarity with AI-assisted development tools (Plus)
• Solid understanding of data quality, validation frameworks, and governance practices
• Strong communication skills, with the ability to work independently and collaborate across technical and business teams

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.

🛫 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.

What are we looking for?

• 4+ years of experience in Data Engineering
• 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 (Must)
• Strong hands-on experience with Python and PySpark (Must)
• hands-on experience in Snowflake-based ETL pipelines (Plus)
• Deep understanding of data pipeline architecture and design patterns
• Experience implementing and scaling CDC (Change Data Capture) patterns
• Strong experience in data modeling for analytics and reporting
• Experience leading initiatives or teams in data engineering environments
• Familiarity with AI-assisted development tools (Plus)
• Solid understanding of data quality, validation frameworks, and governance practices
• Strong communication skills, with the ability to work independently and collaborate across technical and business teams

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