Location: PAN India

Job Title: Senior Data Engineer - GenAI & Unstructured Data Pipelines

Responsibilities:

- Own the end to end ML lifecycle, including data ingestion, feature engineering, training, evaluation, deployment, monitoring, retraining, and rollback
- Design, build, and operate production grade ML pipelines using Azure native services with solid CI/CD and automation practices
- Use Azure Machine Learning and MLflow for experiment tracking, model registry, and governed promotion across Dev/Test/Prod environments
- Design and deploy Generative AI solutions using Azure OpenAI, embeddings, vector search, and RAG pipelines
- Build Agentic AI workflows with multi step reasoning, tool usage, guardrails, observability, reliability, and cost control
- Build scalable data and feature pipelines using Azure Databricks (batch and streaming)
- Build scalable data pipelines for text, documents, logs, and multi-modal data
- Develop RAG pipelines including chunking,



embedding, and retrieval workflows
- Design and manage vector search systems (Azure AI Search, Pinecone, etc.)
- Build batch + real-time data ingestion pipelines using Spark and Kafka

Required Skills:

- 6 8 years of experience in Data Engineering
- Solid hands-on experience with Python / PySpark / SQL
- Apache Spark , Airflow , Kafka
- Handling unstructured data (JSON, logs, documents, PDFs)
- Experience with cloud platforms ( Azure preferred)
- Exposure to LLM / GenAI pipelines (RAG, embeddings, vector DBs)

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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