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Protocol Intelligence
Data-driven signals on your job's competitivenessMetro Bangalore, popular Data Engineer role, known enterprise brand and broad skillset create high competition.
Data engineering skills (ETL, pipelines, databases) are broadly transferable across industries.
Specific data engineering tools and vector/RAG requirements but no explicit years makes shortlisting moderately strict.
Job Description
Structured overview of role & requirementsAbout This Role
Design and scale data pipelines for Retrieval-Augmented Generation (RAG) processing massive unstructured IT logs into vector embeddings.
Manage and optimize vector database infrastructure (e.g., Pinecone, Milvus, Weaviate) to ensure sub-second retrieval speeds for AI reasoning.
Build and maintain CI/CD pipelines for data infrastructure ensuring data quality and real-time context update for AI systems.
Minimum Requirements
Expertise in data mining, data storage, and ETL processes.
Experience developing data pipelines with tools such as Glue, Databricks, Synapse, or Dataproc.
Familiarity with both relational and NoSQL databases like PostgreSQL, DB2, and MongoDB.
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced data engineer with cloud modernization background and strong software engineering skills for production-grade pipeline development.
Skilled in data modeling, building semantic layers, and automating data quality controls relevant to AI context preparation.
Comfortable operating in environments requiring translation of complex technical requirements for AI-driven infrastructure solutions.