Description

Build and maintain scalable data pipelines on Azure for ingestion, transformation, and delivery of datasets.

This role is hybrid.

Responsibilities

• Develop PySpark jobs for scalable data processing and implement efficient transformations.
• Design data models and manage data storage patterns to support analytics and downstream consumption.
• Implement data quality checks, monitoring, and troubleshooting to ensure pipeline reliability.
• Collaborate with analytics and engineering teams to support data requirements and optimize performance.
• Ensure deployment and operational readiness for data pipelines through rigorous monitoring.

Required Skills

• 5+ years of relevant experience in data engineering.
• Strong proficiency with Azure data services and pipeline development on Microsoft Azure.
• Expertise in scalable data processing using PySpark.
• Proven ability in performance tuning for large-scale data transformations.
• Experience with deployment, monitoring, and troubleshooting of data pipelines.
• Relevant degree in Computer Science, Engineering, or a related field.

Preferred Skills

• Experience delivering end-to-end data platform capabilities.
• Background in building robust data models for analytics consumption.

Key Skills

Education

Any Graduate