Data Engineer - On Prem

We’re looking for a skilled Data Engineer with 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 optimize data pipelines and transformations using Python, SQL, and Spark.
• Manage large-scale data storage and processing with Iceberg, Hadoop, and HDFS.
• Develop and maintain dbt models to ensure clean, reliable, and well-structured data.
• Implement robust data ingestion processes, integrating with third-party APIs and 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.