Key Responsibilities
Data Pipeline &
Architecture: Design and build robust ETL/ELT data pipelines using Azure Data Factory, Azure Databricks, and Microsoft Fabric to process batch and real-time streaming data. [1, 2]
AI &
LLM Data Integration: Prepare, clean, and structure enterprise data lakes/lakehouses to feed Azure OpenAI, vector databases, and Retrieval-Augmented Generation (RAG) architectures. [1]
Data Modeling &
Governance: Implement medallion architectures (Bronze, Silver, Gold), ensure data quality, and manage data governance/lineage using tools like Microsoft Purview or Unity Catalog. [1, 2]
Collaboration: Partner with data scientists, AI engineers, and business analysts to operationalize machine learning models and AI agents. [1]

Required Skills &
Qualifications
Cloud Platforms: Hands-on experience with Microsoft Azure (ADF, Azure Databricks, Azure Synapse Analytics, ADLS Gen2, and Microsoft Fabric).
Programming &
Querying: Advanced proficiency in Python, PySpark, Spark SQL, and complex SQL.
AI &
GenAI Familiarity: Knowledge of vector embeddings, semantic search, prompt grounding, and integrating Azure AI / OpenAI endpoints.

📌 Azure Data Engineer + Ai 21 Aug Friday Bengaluru Video Interview
🏢 Tata Consultancy Services
📍 Bengaluru