Data Engineer

About the role

As an AI Data Engineer at Kyndryl, you'll be the architect behind the high-performance data infrastructure that powers our autonomous systems. We aren't just moving tables; we're building the real-time pipelines that allow agentic AI to reason over the world's most complex enterprise environments.

What you will do

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

Who You Are

You're good at what you do and possess the required experience to provide it. You have a growth mindset—keen to drive your own personal and professional development. You are customer-focused—someone who prioritizes customer success in your work. You're open and borderless—naturally inclusive in how you work with others.

Required Skills and Experience

• 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

Preferred Skills and Experience

• Experience working as a Data Engineer and/or in cloud modernization
• Experience in Data Modelling, to create conceptual model of how data is connected and how it will be used in business processes
• Professional certification, e.g. Open Certified Technical Specialist with Data Engineering Specialization
• 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
• Understanding of social coding and Integrated Development Environments, e.g. GitHub and Visual Studio
• Degree in a scientific discipline, such as Computer Science, Software Engineering, or Information Technology

Pay

The compensation range for the position in the U.S. is $63,360 to $114,120 based on a full-time schedule, with location-specific ranges for California (San Francisco Bay Area: $76,080 to $137,040; All Other: $69,720 to $125,640), Colorado ($63,360 to $114,120), Massachusetts ($63,360 to $125,640), New York City ($76,080 to $137,040), Washington ($69,720 to $125,640), and Washington DC ($69,720 to $125,640). Actual compensation may vary depending on geography, job-related skills, and experience. For part-time roles, compensation will be adjusted appropriately. This position is also eligible for Kyndryl's discretionary annual bonus program, based on performance and subject to applicable plan terms.

Benefits

You may receive a comprehensive benefits package which includes medical and dental coverage, disability, retirement benefits, paid leave, and paid time off.