Data Engineering

Kyndryl

AI Data Engineer designing RAG pipelines, vector databases, semantic layers, and data guardrails. Building reliable CI/CD infrastructure for Kyndryl’s mission-critical enterprise technology systems.

Posted 9/7/2026full-timeLima • 🇵🇪 PeruMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and scaling Retrieval-Augmented Generation (RAG) pipelines, transforming unstructured data into optimized vector embeddings, and maintaining vector databases. Proficient in building and deploying CI/CD pipelines while ensuring data quality and context for effective data infrastructure management.

Highest-signal resume keywords

Data MiningExtract-Transform-Load (ETL)CI/CD Pipeline DevelopmentRelational and NoSQL DatabasesData Engineering Certification

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data StorageData Pipeline DevelopmentVector EmbeddingsKnowledge GraphsData Quality ManagementData ModellingAutomated Data GuardrailsProblem-SolvingAnalytical SkillsCritical Thinking

Soft Skills

Attention to DetailCommunication SkillsCollaboration

Tools & Technologies

PineconeMilvusWeaviateGlueDatabricksSynapseDataprocPostgreSQLDB2MongoDB

Certifications & Qualifications

Open Certified Technical Specialist with Data Engineering SpecializationAWS Certified Data Analytics – SpecialtyElastic Certified EngineerGoogle Cloud Professional Data EngineerMicrosoft Certified: Azure Data Engineer Associate

Industry Keywords

Cloud ModernizationSocial CodingIntegrated Development EnvironmentsScientific DisciplineComputer ScienceSoftware EngineeringInformation Technology

Tech Stack

Tools & technologies

AWSAzureCloudETLMongoDBNoSQLPostgres

About the role

Key responsibilities & impact

Design and scale Retrieval-Augmented Generation (RAG) pipelines
Transform unstructured IT logs and documentation into optimized vector embeddings
Maintain the health and performance of vector databases such as Pinecone, Milvus, or Weaviate
Build knowledge graphs and semantic layers for AI agents
Create automated data guardrails to detect noise, bias, and personally identifiable information
Identify and resolve data-quality issues at the source
Build, deploy, and maintain CI/CD pipelines for data infrastructure
Ensure data context remains fresh and reliable
Collaborate with technical and non-technical colleagues to derive technical requirements from business needs

Requirements

What you’ll need

Expertise in data mining, data storage, and Extract-Transform-Load (ETL) processes
Experience developing data pipelines and using tooling such as Glue, Databricks, Synapse, or Dataproc
Experience with relational and NoSQL databases, including PostgreSQL, DB2, and MongoDB
Excellent problem-solving, analytical, and critical-thinking skills
Ability to manage multiple projects simultaneously with attention to detail
Ability to communicate with technical and non-technical colleagues and translate business needs into technical requirements
Preferred: experience as a Data Engineer and/or in cloud modernization
Preferred: experience in data modelling
Preferred: professional certification, such as Open Certified Technical Specialist with Data Engineering Specialization
Preferred: cloud platform certification, such as AWS Certified Data Analytics – Specialty, Elastic Certified Engineer, Google Cloud Professional Data Engineer, or Microsoft Certified: Azure Data Engineer Associate
Preferred: understanding of social coding and integrated development environments, such as GitHub and Visual Studio
Preferred: degree in a scientific discipline such as Computer Science, Software Engineering, or Information Technology

Benefits

Comp & perks

Flexible, supportive environment
Well-being prioritized
Hybrid-friendly culture
Be Well programs supporting financial, mental, physical, and social health
Personalized development goals and continuous feedback
Cutting-edge learning opportunities
Certifications with Microsoft, Google, and Amazon
Coaching and hands-on experiences
Career-path and professional development tools
Employee referral opportunity