Design and implement end-to-end data architectures for enterprise analytics and operations.
Build and optimize data pipelines using Python, SQL, and Spark across on-premise and cloud
Manage large-scale storage and processing with Iceberg, Hadoop, and HDFS.
Develop and maintain dbt models for clean, reliable data structures.
Implement robust data ingestion from third-party APIs and on-premise systems.
Collaborate with cross-functional teams to align business and technical goals.

🎯 Requirements

4+ years in data engineering, including at least 1 year 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; able to work independently with technical and non-technical
Master’s degree in Data Science or related field.

🎁 Benefits

Apply on employer's website

This employer gathers applications via their own applicant tracking system.

You will be redirected to an external application form.

Share job

Meet JobCopilot: Your Personal AI Job Hunter

Automatically Apply to Engineering Jobs. Just set your preferences and Job Copilot will do the rest — finding, filtering, and applying while you focus on what matters.

Activate JobCopilot