We are seeking a Subject Matter Expert (SME) in Azure Data & AI to drive the technical depth, accuracy, and instructional value of our training content.

Youll lead the definition and review of presentations, labs, and real-world scenarios on Azures modern data and AI stack, working closely with content creators to shape advanced, certification-aligned learning experiences.

Key Responsibilities :

- Define and validate learning content aligned to DP-203, AI-102, and DP-100 certification paths.

- Provide technical guidance on Azure data pipelines, lakehouse architecture, and ML/AI integration.

- Design and review labs and walkthroughs using Synapse, Data Factory, Databricks, and Cognitive Services.

- Translate AI/ML concepts (e.g., model lifecycle, prompt engineering, RAI) into structured training materials.

- Stay current with Microsofts evolving data/AI ecosystem including OpenAI integration and Fabric convergence.

- Ensure quality, realism, and accuracy across all deliverables, collaborating with writers and stakeholders.

Required Skills :

- Deep hands-on experience in :

1. Data : Azure Synapse, Data Factory, Databricks, Data Lake Gen2, Cosmos DB, Event Hub.

2. AI : Azure OpenAI, Cognitive Services, Azure Machine Learning Studio, Responsible AI.

- 7+ years in roles such as data engineer, ML engineer, AI architect, or applied data scientist.

- Proficient with Spark, Python, SQL, and REST APIs.

- Strong grasp of AI-based application architecture, ethical AI practices, and cloud-scale data governance.

- Ability to bridge technical concepts for instructional teams and content developers.

Good-to-Have :

- Certifications : DP-203, AI-102, DP-100 (preferred, not mandatory).

- Experience building or validating technical training content.

- Familiarity with GitHub, markdown, Jupyter Notebooks, or SCORM.

- Experience with prompt engineering and Azure OpenAI orchestration tools (e.g., LangChain, Semantic Kernel).