SENIOR DATA ENGINEER
TE Connectivity (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 25–40 LPA
Posted 19h ago
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Job description
Structured overview of role & requirements
About This Role
- Design and develop scalable, secure data pipelines for structured and unstructured enterprise data tailored to AI/Generative AI applications.
- Build and maintain AI-ready datasets, embedding workflows, vector search solutions, and knowledge graph data architectures for enterprise AI initiatives.
- Integrate data securely across Azure, Databricks, cloud storage, enterprise databases, and APIs to support production-grade AI data solutions.
Minimum Requirements
- Proficient in Python and SQL with strong data processing and API integration skills.
- Experienced in developing scalable data pipelines using Databricks, PySpark, or equivalent cloud data platforms.
- Knowledge of AI data domains including Retrieval-Augmented Generation (RAG), embeddings, vector search technologies (e.g., Azure AI Search, FAISS).
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in engineering AI/Generative AI data solutions handling structured, semi-structured, and unstructured data at scale.
- Capability to implement data governance, security, and production monitoring specifically for AI datasets.
- Comfortable working with modern cloud platforms (Azure), vector databases, and collaborating cross-functionally with AI/ML and business teams.