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 skilledSenior Data Engineerwith strong experience in distributed systems, Python/Scala, and modern data engineering tools to help design and implement an end-to-end data architecture for a leading enterprise client. This role is part of a strategic initiative to enable robust analytics, BI, and operational workflows across both on-premise and cloud environments.

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 analytics, reporting, and business decision-making.

This position is ideal for engineers with a strong data foundation who are looking to apply their skills in large-scale, modern data environments, while gaining exposure to advanced architectures and tooling.

You will:

• Design and implement an end-to-end data solution architecture tailored to enterprise analytics and operational needs.

• Build, maintain, and optimizedata pipelines and transformationsusingPython, SQL, and Spark.

• Manage large-scale data storage and processing withIceberg, Hadoop, and HDFS.

• Develop and maintaindbt modelsto ensure clean, reliable, and well-structured data.

• Implement robustdata ingestion processes, integrating withthird-party APIsand on-premise systems.

• Collaborate with cross-functional teams to align on business goals and technical requirements.

• Contribute to documentation and continuously improve engineering and data quality processes.

• 4+ years of experience indata engineering, including at least1 year with on-premise systems.

• Proficiency inPythonfor data workflows and pipeline development.

• Strong experience withSQL, Spark, Iceberg, Hadoop, HDFS, and dbt.

• Familiarity withthird-party APIsand data ingestion processes.

• Excellent communication skills, with the ability to work independently and engage effectively with both technical and non-technical stakeholders.

• Master's degree inData Scienceor a related field.

• Experience withAirflowor other orchestration tools.

• Hands-on experience withCursor, Copilot, or similar AI-powered developer tools.