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Kyndryl

Data Engineer

Kyndryl

AI Data Engineer responsible for designing data infrastructure and pipelines at Kyndryl. Transforming unstructured IT logs into optimized vector embeddings.

Posted 7/8/2026full-timeBogota • 🇨🇴 ColombiaMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and scaling data pipelines for Retrieval-Augmented Generation (RAG) while ensuring optimal performance of vector databases. Proficient in data mining, ETL processes, and building automated data guardrails to maintain data quality and integrity.

Highest-signal resume keywords
Data MiningETL ProcessesData Pipeline DevelopmentVector Database ManagementData Modeling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data MiningETL ProcessesData Pipeline DevelopmentData ModelingRelational DatabasesNoSQL DatabasesVector EmbeddingsAutomated Data GuardrailsCI/CD PipelinesKnowledge Graphs
Soft Skills
Problem-SolvingAnalytical ThinkingAttention to DetailCommunication SkillsProject Management
Tools & Technologies
GlueDatabricksSynapseDataprocPostgreSQLDB2MongoDBPineconeMilvusWeaviate
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 ModernizationSemantic LayersKnowledge GraphsData QualityPII Detection

Tech Stack

Tools & technologies
AWSAzureCloudETLMongoDBNoSQLPostgres

About the role

Key responsibilities & impact
  • Architect for RAG: Design and scale the pipelines for Retrieval-Augmented Generation (RAG), transforming massive volumes of unstructured IT logs and documentation into optimized Vector Embeddings
  • Scale vector infrastructure: Responsible for the health and performance of our vector databases (e.g., Pinecone, Milvus, or Weaviate), ensuring sub-second retrieval speeds for agentic reasoning loops
  • Engineer semantic layers: Move beyond simple ETL to build knowledge graphs and semantic layers that provide agents with the necessary context to navigate complex infrastructure puzzles
  • Automate data excellence: Build automated data guardrails to detect noise, bias, or PII (Personally Identifiable Information) before it reaches the model
  • Solve meaningful challenges: Serve as the bridge between raw, messy data sources and deep technical AI work, identifying and resolving quality issues at the source
  • Progress to production: Build, deploy, and maintain the CI/CD pipelines for our data infrastructure, ensuring that our context window remains fresh and reliable

Requirements

What you’ll need
  • Expertise in data mining, data storage and Extract-Transform-Load (ETL) processes
  • Experience in data pipelines development and tooling, e.g., Glue, Databricks, Synapse, or Dataproc
  • Experience with both relational and NoSQL databases, PostgreSQL, DB2, MongoDB
  • Excellent problem-solving, analytical, and critical thinking skills
  • Ability to manage multiple projects simultaneously, while maintaining a high level of attention to detail
  • Ability to communicate with both technical and non-technical colleagues, to derive and translate technical requirements from business needs
  • Experience working as a Data Engineer and/or in cloud modernization (preferred)
  • Experience in Data Modelling, to create conceptual model of how data is connected and how it will be used in business processes (preferred)
  • Professional certification, e.g. Open Certified Technical Specialist with Data Engineering Specialization (preferred)
  • Cloud platform certification, e.g. 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, e.g. GitHub and Visual Studio (preferred)
  • Degree in a scientific discipline, such as Computer Science, Software Engineering, or Information Technology (preferred)

Benefits

Comp & perks
  • Flexible, supportive environment
  • Be Well programs designed to support financial, mental, physical, and social health
  • Access to cutting-edge learning opportunities
  • Continuous feedback to keep you inspired and on track