Azure Databricks Engineer

Role Overview

We are seeking a highly skilled Azure Databricks Engineer with expertise in building scalable data platforms on Microsoft Azure and experience working with Azure AI Foundry to support advanced analytics, machine learning, and Generative AI solutions. The ideal candidate will have strong data engineering fundamentals, hands-on experience with Azure cloud services, and the ability to design and implement end-to-end data pipelines that enable AI-driven business solutions.

Key Responsibilities

• Design, develop, and optimize scalable data pipelines using Azure Databricks.
• Build and maintain data ingestion frameworks from structured and unstructured data sources.
• Develop ELT/ETL processes using PySpark, Spark SQL, and Delta Lake.
• Implement modern data architectures including Data Lakehouse solutions.
• Integrate enterprise data platforms with Azure AI Foundry to enable AI and Generative AI use cases.
• Support AI/ML model development by preparing, transforming, and managing training datasets.
• Develop and manage data workflows using Azure Data Factory (ADF).
• Build data quality, validation, monitoring, and governance frameworks.
• Collaborate with Data Scientists, AI Engineers, Architects, and Business Stakeholders to deliver scalable AI solutions.
• Implement CI/CD pipelines and DevOps best practices for data engineering workflows.
• Ensure compliance with data security, privacy, and governance standards.

Requirements & Tech Stack

Azure Data Engineering

• Azure Databricks
• PySpark
• Spark SQL
• Delta Lake
• Azure Data Lake Storage (ADLS Gen2)
• Azure Data Factory (ADF)
• Azure Synapse Analytics
• Azure SQL Database
• Data Modeling

Programming

• Python
• SQL
• Scala (Preferred)

Azure Platform

• Azure Storage Services
• Azure Key Vault
• Azure Monitor
• Azure Functions
• Azure Logic Apps

DevOps & Deployment

• Azure DevOps
• Git
• CI/CD Pipelines
• Infrastructure as Code (Terraform preferred)

Azure AI Foundry / AI Experience

• Experience working with Azure AI Foundry and Azure AI Services.
• Understanding of LLMs, RAG (Retrieval Augmented Generation), Vector Databases, Embeddings, and Prompt Engineering.
• Experience building data pipelines that feed AI and GenAI applications.
• Knowledge of Azure OpenAI integration patterns.
• Exposure to AI model lifecycle management and monitoring.
• Experience integrating enterprise knowledge repositories with AI applications.
• Understanding of AI governance, security, and responsible AI principles.

Qualifications

• Bachelor's or master's degree in computer science, Engineering, Data Science, Information Technology, or related field.

Preferred Qualifications

• Experience with Microsoft Fabric.
• Experience with Vector Databases such as Azure AI Search, Pinecone, or Chroma.
• Exposure to MLflow and MLOps frameworks.
• Familiarity with Kubernetes and containerization.
• Knowledge of real-time streaming using Spark Structured Streaming or Kafka.
• Experience supporting conversational AI or GenAI use cases.

Nice-to-Have Certifications

• Microsoft Certified: Azure Data Engineer Associate (DP-203)
• Microsoft Certified: Azure AI Engineer Associate (AI-102)
• Databricks Certified Data Engineer Associate/Professional
• Microsoft Azure Solutions Architect Expert