Azure Data Engineer

About Cloudaeon:

Cloudaeon is a global technology consulting and services company helping enterprises modernize and manage their cloud infrastructure, big data ecosystems, DevOps pipelines, and advanced analytics platforms. We deliver high-quality, scalable solutions built on deep domain expertise and leading enterprise data technologies.

Our teams work actively on AI and GenAI initiatives, incorporating machine learning, intelligent automation, and modern data engineering practices to create future-ready digital solutions. With a highly skilled global team committed to excellence, we consistently exceed customer expectations and help organizations achieve their strategic goals.

Job Role Azure Data Engineer Experience – 3 to 7 years Location: Pune (Hybrid)

Job description:

We are seeking an Azure Data Engineer with strong hands-on experience in data pipelines and Azure services. The role includes exposure to AI/ML concepts and Databricks AI, enabling a gradual transition into AI engineering.

Responsibilities

• Build and maintain ETL/ELT pipelines using ADF, Databricks, PySpark, and SQL.
• Implement data transformations across Bronze, Silver, Gold layers.
• Assist in modernizing data platforms using Azure Data Services.
• Configure and support Databricks, Delta Lake, and Unity Catalog.
• Implement pipeline monitoring, optimization, and DevOps automation.
• Understand business requirements and translate them into technical execution.
• (AI-related) Prepare datasets for AI/ML and support feature engineering in Databricks AI.
• (AI-related) Learn fundamentals of embeddings, vector stores, MLflow, and model workflows.

Requirements

• 3+ years of experience in Azure Data Engineering (ADF, Databricks, PySpark, SQL).
• Good understanding of data warehousing, modelling, and SQL.
• Hands-on experience with ADLS, Delta Lake, Synapse, and pipeline deployments.
• Experience working with DevOps and CI/CD workflows.
• Strong communication, problem-solving abilities, and teamwork.
• Passion for learning and continuous improvement.
• Basic understanding of Databricks AI, MLflow, model workflows, and AI fundamentals.
• Nice to have: Exposure to Azure Machine Learning, Azure OpenAI, and AI/ML model integration.