Description

Lead data engineering efforts within the Azure ecosystem, owning the full lifecycle of data platforms and ML workflows.

This role is on-site.

Responsibilities

• Develop and maintain scalable data pipelines using Databricks and Azure Data Factory.
• Implement and deploy machine learning workflows leveraging Azure ML and Databricks ML.
• Manage efficient data storage and retrieval strategies using Parquet and Delta tables.
• Utilize Azure SDK and Synapse Analytics to support and evolve data architecture requirements.
• Collaborate on defining best practices for cloud-native data engineering within the Azure environment.

Required Skills

• 5+ years of professional experience in data engineering.
• Proficiency in Python and SQL for data manipulation and logic.
• Hands-on experience with Databricks for big data processing.
• Experience building and managing pipelines with Azure Data Factory.
• Working knowledge of Azure ML and Databricks ML for model deployment.
• Experience using Azure SDK for custom integrations and automation.
• Experience with Synapse Analytics for enterprise data warehousing.
• Knowledge of Parquet and Delta tables for optimized data storage.
• Bachelor's degree or equivalent graduate-level education.

Key Skills

Education

Any Graduate