Data Engineer
Kyndryl (company site, opens in a new tab)6+ yrsBengaluruOn-siteDirect career pageEst. 18–30 LPA
Posted 12h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and optimize scalable data pipelines and cloud-native data solutions on Google Cloud Platform (GCP).
- Build and maintain real-time data infrastructure for agentic AI, including retrieval-augmented generation (RAG) pipelines and vector database performance (using Pinecone, Milvus, or Weaviate).
- Develop semantic layers, knowledge graphs, and automated data guardrails to ensure data quality and safety; maintain CI/CD pipelines for data infrastructure.
Minimum Requirements
- 6+ years of IT experience with expertise in ETL/ELT processes and data pipeline development (tools like Glue, Databricks, Synapse, or Dataproc).
- Experience with relational and NoSQL databases such as PostgreSQL, DB2, and MongoDB.
- Proficiency in DBT, GCP (including BigQuery), Terraform, CI/CD, SQL, and data modeling techniques.
- Work Experience Required: Minimum 6 years in IT; Notice period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in cloud modernization and data engineering with strong software engineering skills for building and deploying production-grade data infrastructure.
- Skilled at translating complex business needs into scalable data solutions, focusing on AI-powered data products and infrastructure.
- Holds relevant certifications (e.g., Google Cloud Professional Data Engineer, AWS Data Analytics Specialty) and has hands-on experience with modern data architectures and tools.