Data Engineer (OnPrem)

We’re looking for a skilled

Senior Data Engineers / Data Engineers

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.

Qualifications

2+ years of experience in

data engineering , including at least

1 year with on-premise systems .

Proficiency in

Python

for data workflows and pipeline development.

Strong experience with

SQL, Spark, Iceberg, Hadoop, HDFS, and dbt .

Familiarity with

third-party APIs

and data ingestion processes.

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

Preferred Qualifications

Master’s degree in

Data Science

or a related field.

Experience with

Airflow

or other orchestration tools.

Hands-on experience with

Cursor, Copilot, or similar AI-powered developer tools .