Senior Data Engineer

Blend360

About The Position

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. 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.

Requirements

3+ years of experience in Data Engineering
Strong hands-on experience with Snowflake (Must)
Experience building and maintaining data pipelines in AWS (Must)
Strong experience building ELT pipelines and data ingestion solutions
Strong experience with Airflow for workflow orchestration (Must)
Solid experience with SQL and large-scale data processing
Experience with data quality, validation frameworks, and governance practices

Nice To Haves

Familiarity with Snowflake Cortex (Plus)
Experience with CI/CD pipelines for data workflows (Plus)
Experience with Iceberg tables and Snowflake data sharing (Plus)
Experience with tools such as dbt, Glue, Athena, EMR, Lambda, Terraform, or CloudFormation (Plus)

Responsibilities

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, and data quality issues, and implement mitigation strategies before they impact delivery.
Contribute to data governance initiatives, including data definitions, lineage, and stewardship practices.
Drive documentation and continuous improvement of data platform processes.

Benefits

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.
Career development plans and mentorship programs to help shape your path.
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.