Azure Developer

Senior Azure Developer

Position Overview

We are seeking a visionary and hands-on Senior Azure Developer

to lead the design, development, and modernization of our enterprise data platforms. In this role, you will be the core strategist bridging the gap between traditional data engineering and modern Generative AI / Machine Learning initiatives. You will architect robust, scalable, and secure cloud data solutions that empower our AI models, business intelligence tools, and advanced analytics applications.

Key Responsibilities

1. Data Architecture & Modernization

• Design and implement end-to-end cloud data lake houses, data warehouses, and streaming pipelines using the Microsoft Azure stack.
• Lead the transition from legacy on-premises or siloed data systems to a unified, AI-ready data infrastructure.
• Define data models (dimensional, vault, and relational) optimized for both analytical queries and AI model training.

2. AI & Advanced Analytics Readiness

• Architect data foundations specifically designed to support Azure OpenAI, Large Language Models (LLMs), and RAG (Retrieval-Augmented Generation) patterns.
• Build semantic search infrastructures using Azure AI Search (formerly Cognitive Search) to enable vector embeddings and cognitive indexing.
• Collaborate with Data Scientists and AI Engineers to operationalize machine learning models through robust MLOps pipelines.

3. Data Engineering & Integration

• Develop scalable ingestion and transformation patterns using Azure Data Factory, Azure Databricks, and Microsoft Fabric.
• Implement real-time processing architectures using Azure Event Hubs, IoT Hubs, or Azure Stream Analytics.
• Enforce clean code practices in PySpark, SQL, Python, and Scala within notebook-driven environments.

4. Governance, Security & Compliance

• Establish stringent data governance policies utilizing Microsoft Purview for data lineage, classification, and cataloging.
• Implement enterprise-grade security including Role-Based Access Control (RBAC), row/column-level security, Azure Key Vault integration, and data encryption (at rest and in transit).
• Ensure compliance with international and industry standards (e.g., GDPR, HIPAA, SOC2).

5. FinOps & Performance Optimization

• Monitor and optimize Azure consumption costs using Azure Cost Management, ensuring efficient scaling of compute clusters (Databricks/Fabric).
• Tune performance of complex queries, indexing strategies, and partition schemes across Azure Synapse, Delta Lakes, and Azure SQL databases.

Required Technical Skills

Core Azure Stack

• Data Integration & Storage: Microsoft Fabric, Azure Synapse Analytics, Azure Databricks, Azure Data Lake Storage (ADLS Gen2), Cosmos DB.
• AI & Machine Learning: Azure OpenAI Service, Azure AI Search, Azure Machine Learning (Azure ML).
• Governance & Orchestration: Microsoft Purview, Azure Data Factory (ADF).

Languages & Frameworks

• Programming/Querying: Python, SQL, PySpark, Scala, PowerShell.
• Data Formats: Delta Lake, Parquet, Avro, JSON.

DevOps & Infrastructure

• CI/CD & IaC: Azure DevOps, GitHub Actions, Terraform, ARM Templates, or Bicep.
• Containerization: Docker, Azure Kubernetes Service (AKS).

Qualifications & Experience

• Experience: 4+ years in Data Engineering/Architecture, with at least 2+ years of dedicated experience architecting native Azure data solutions.

• AI Exposure: Proven track record of architecting data pipelines that feed into production-grade AI/ML or GenAI applications.

• Education: Bachelors or Master’s degree in Computer Science, Data Science, Information Technology, or a related field.

• Certifications (Highly Preferred):

• Microsoft Certified: Azure Data Engineer Associate (DP-203)

• Microsoft Certified: Azure Solutions Architect Expert (AZ-305)

• Microsoft Certified: Azure AI Engineer Associate (AI-102) or Fabric Analytics Engineer (DP-600)

Soft Skills & Leadership

• Strategic Thinker: Ability to align data initiatives directly with overarching business goals and AI transformation roadmaps.
• Collaborative Communicator: Capable of translating complex architectural concepts to non-technical stakeholders and C-suite executives.
• Mentor: Passion for coaching junior data engineers and promoting a continuous learning culture.