Description

You will design and build scalable data infrastructure on Azure, owning the full lifecycle from ingestion to analytical data products.

This role is on-site.

Responsibilities

• Design and implement metadata-driven frameworks for data ingestion, quality, and transformation across batch and streaming datasets.
• Develop and optimize end-to-end data pipelines to process structured and unstructured data.
• Build exception handling, logging, and monitoring mechanisms for operational support.
• Take ownership of complex modules and lead the development of critical data workflows.
• Collaborate with cross-functional teams to deliver impactful analytics solutions.

Required Skills

• 5-10 years of total IT experience, including 3+ years in big data engineering on Microsoft Azure.
• Strong SQL expertise with experience in Azure SQL, Synapse, or similar cloud databases.
• Proven experience building high-performance data pipelines using Azure Databricks (PySpark, Spark SQL).
• Hands-on experience with Azure Data Factory for pipeline orchestration.
• Experience with batch and streaming data processing.
• Delivered at least one end-to-end Data Lakehouse solution (Medallion Architecture).
• Strong programming and debugging skills in Python, PySpark, and SQL.

Preferred Skills

• Knowledge of data governance, security, and lifecycle management.

Key Skills

Education

Any Graduate