Blend360

Technology

SeniorDataEngineer

$15000–25000k ~AI est. Buenos Aires, Buenos Aires, Argentina FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for mid candidates.

The Brief

“Senior Data Engineer at Blend360. Skills: Data Engineering, Snowflake, AWS, Airflow. Lead design and implementation of data ingestion architectures. Own development of end-to-end ELT pipelines”

Industry & Context.

Technology
Problems you'll solve

Mitigation strategies

What They're Looking For.

Must Have

3+ years of experience in Data Engineering, Hands-on experience with Snowflake, Experience building and maintaining data pipelines in AWS, Experience building ELT pipelines, Experience with Airflow for workflow orchestration, Solid experience with SQL, Large-scale data processing experience

Nice to Have

Familiarity with Snowflake Cortex, Experience with CI/CD pipelines, Experience with Iceberg tables, Experience with Snowflake data sharing, Experience with dbt, Experience with Glue, Experience with Athena, Experience with EMR, Experience with Lambda, Experience with Terraform, Experience with CloudFormation

What You'll Do.

Lead design and implementation of data ingestion architectures

Own development of end-to-end ELT pipelines

Integrate multiple data sources

Design and manage workflow orchestration using Airflow

Ensure efficient scheduling

Ensure dependency management

Design and enforce data quality frameworks

Build and optimize data pipelines on AWS

Build and optimize data architectures on AWS

Develop and enhance data validation frameworks

Develop and enhance data ingestion frameworks

Act as a technical leader

Guide best practices in data engineering

Guide best practices in orchestration

Guide best practices in governance

Guide best practices in pipeline reliability

Proactively identify risks

Proactively identify bottlenecks

Proactively identify data quality issues

Implement mitigation strategies

Contribute to data governance initiatives

Drive documentation of data platform processes

Drive continuous improvement of data platform processes

How You'll Work.

Team & Collaboration

Client-facing role

Communication Scope

Communication skills

Full Job 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 [www.blend360.com](http://www.blend360.com/) We’re looking for a Senior Data Engineer with strong expertise in Snowflake-based data platforms, AWS, and Airflow, to lead the design and implementation of scalable ingestion and orchestration solutions for a leading enterprise client. This is a client-facing role, ideal for engineers who combine deep technical expertise with strong communication skills and a proactive mindset. You will play a key role in ensuring high-quality, governed, and reliable data pipelines that power critical business and analytics workflows. What will you be doing? * Lead the design and implementation of data ingestion architectures in Snowflake, ensuring scalability and reliability. * Own the development of end-to-end ELT pipelines integrating multiple data sources. * Design and manage workflow orchestration using Airflow, ensuring efficient scheduling, monitoring, and dependency management. * Design and enforce data quality frameworks, including validation rules, testing strategies, and monitoring. * Build and optimize data pipelines and architectures on AWS (S3, Glue, Lambda, EMR, etc.). * Develop and enhance data validation and ingestion frameworks. * Act as a technical leader, guiding best practices in data engineering, orchestration, governance, and pipeline reliability. * Proactively identify risks, bottlenecks, a

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