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 - 12th Aug (Wednesday) - Bengaluru- Virtual
🏢 Tata Consultancy Services
📍 Bengaluru