Data Engineer
Kyndryl (company site, opens in a new tab)6+ yrsBengaluruOn-siteDirect career pageEst. 14–26 LPA
Posted 10h 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).
- Architect and maintain high-performance vector databases and pipelines for Retrieval-Augmented Generation (RAG) enabling real-time AI reasoning.
- Build and deploy CI/CD pipelines, automate data quality guardrails, and bridge raw data sources to AI-ready datasets with semantic layers and data modeling.
Minimum Requirements
- 6+ years overall IT experience with strong data engineering expertise including ETL, data storage, and pipeline development.
- Proficiency with data pipeline tools such as Glue, Databricks, Synapse, or Dataproc and relational & NoSQL databases (PostgreSQL, DB2, MongoDB).
- Experience with cloud and DevOps practices including Infrastructure as Code (Terraform) and CI/CD.
- Work Experience Required: 6+ years in IT with hands-on data engineering roles.
Ideal Candidate Profile
- Experienced in modern data architecture with expertise in DBT, GCP services, BigQuery, and vector databases for AI applications.
- Able to architect and scale AI-focused data infrastructures including semantic layers and knowledge graphs in complex enterprise environments.
- Demonstrated capability in building production-ready data pipelines with automated data quality controls and cloud-native tooling integrated into CI/CD workflows.