Description

You will design, develop, and maintain scalable data pipelines across the Microsoft Azure ecosystem to support analytics and AI/ML initiatives.

This role is hybrid.

Responsibilities

• Build and orchestrate ETL/ELT workflows using Azure Data Factory.
• Develop and optimize data processing solutions using Azure Databricks and distributed computing frameworks.
• Design enterprise-grade data models, including dimensional, relational, and Lakehouse architectures.
• Enable AI/ML initiatives by curating datasets and integrating Azure Machine Learning pipelines.
• Ensure data governance, security, and quality while optimizing pipeline reliability and cost efficiency.

Required Skills

• 8–10 years of experience in Data Engineering or Data Platform Engineering.
• Hands-on expertise with Azure Data Factory for orchestration and automation.
• Experience with Azure Databricks for large-scale data transformation and processing.
• Strong proficiency in SQL and Python for data engineering workflows.
• Experience working with Azure Data Lake Storage (ADLS) and modern Lakehouse architectures.
• Familiarity with Azure Machine Learning pipelines and supporting feature/data workflows.
• Strong understanding of data governance, lineage, and quality frameworks.
• Experience contributing to CI/CD automation for enterprise data workflows.

Key Skills

Education

Any Graduate