Data Engineer

Blend360 is seeking a skilled Data Engineer with a strong background in distributed systems, Python/Scala, and modern data engineering tools to contribute to the design and implementation of an end-to-end data architecture for a prominent enterprise client. This role is integral to a strategic initiative aimed at establishing robust analytics, BI, and operational workflows across both on-premise and cloud environments. You will collaborate with Blend's internal teams and client stakeholders to build and optimize data pipelines, support data modeling, and ensure the reliability of data flows for analytics, reporting, and business decision-making. This opportunity is perfect for data engineers with a solid foundation who wish to apply their skills in large-scale, contemporary data environments and gain exposure to advanced architectures and tooling.

Key Responsibilities:

• Design and implement comprehensive data solution architectures tailored to enterprise analytics and operational requirements.
• Develop, maintain, and optimize data pipelines and transformations using Python, SQL, and Spark.
• Manage large-scale data storage and processing utilizing Iceberg, Hadoop, and HDFS.
• Build and maintain dbt models to ensure data accuracy, reliability, and structure.
• Implement efficient data ingestion processes, integrating with third-party APIs and on-premise systems.
• Collaborate with cross-functional teams to align on business objectives and technical specifications.
• Contribute to documentation and continuously enhance engineering and data quality processes.

Required Qualifications:

• A minimum of 2 years of experience in data engineering, with at least 1 year focusing on on-premise systems.
• Proficiency in Python for developing data workflows and pipelines.
• Solid experience with SQL, Spark, Iceberg, Hadoop, HDFS, and dbt.
• Familiarity with third-party APIs and data ingestion methodologies.
• Excellent communication skills, with the ability to work autonomously and engage effectively with both technical and non-technical stakeholders.

Preferred Qualifications:

• A Master’s degree in Data Science or a related field.
• Experience with orchestration tools such as Airflow.
• Hands-on experience with AI-powered developer tools like Cursor or Copilot.