Senior Data Analytics & Knowledge Engineer AWS Agentic AI

Compunnel

$130K — $155K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years experience in AWS technologies including Bedrock, Neptune, and OpenSearch.
  • Deep understanding of knowledge graphs and ontologies using RDF, OWL, SKOS, and Turtle.
  • Proficiency in programming with Python and SQL.
  • Experience with AWS Glue, Amazon S3, and Apache Iceberg for data engineering tasks.
  • Familiarity with frameworks such as LangChain and LlamaIndex for LLM/RAG integration.
  • Ability to implement Text2SQL capabilities effectively.
  • Strong background in both data engineering and agentic AI solutions.

Responsibilities

  • Design and build AWS Agentic AI solutions using advanced AWS technologies.
  • Develop and manage knowledge graphs and ontologies for data organization.
  • Optimize data engineering processes with Python, SQL, and AWS tools.
  • Integrate LLM and RAG solutions within existing data frameworks.
  • Establish Text2SQL functionalities for enhanced user interaction with data.
  • Create and sustain efficient data pipelines that support AI applications.
  • Work closely with cross-functional teams to align data solutions with business needs.

Benefits

  • Opportunities for professional development and training.
  • Access to the latest AWS tools and technologies.
  • Flexible work environment promoting work-life balance.
  • Collaborative team culture focused on innovation.
  • Potential for cross-industry experience in cutting-edge AI applications.
Full Job Description
Job Summary

We are seeking a Senior Data Analytics & Knowledge Engineer to support AWS Agentic AI solutions, with a strong focus on data engineering, knowledge graphs, and LLM/RAG integration. The ideal candidate will have hands-on experience with AWS Bedrock, Amazon Neptune, OpenSearch vector search, knowledge graphs, ontologies, and modern data engineering technologies. Life Sciences or Healthcare domain experience is preferred.

Key Responsibilities
• Design, develop, and support AWS Agentic AI solutions leveraging AWS Bedrock, Amazon Neptune, and OpenSearch for vector search and RAG capabilities.
• Develop and maintain knowledge graphs and ontologies using standards and technologies such as RDF, OWL, SKOS, and Turtle.
• Build and optimize data engineering solutions using Python, SQL, AWS Glue, Amazon S3, and Apache Iceberg.
• Develop and integrate LLM and RAG solutions using frameworks such as LangChain, LlamaIndex, and Strands Agents.
• Implement Text2SQL capabilities and integrate natural language interfaces with data platforms.
• Design and maintain data pipelines and knowledge infrastructure supporting AI and analytics use cases.
• Integrate data engineering capabilities with LLM, RAG, and agentic AI architectures.
• Collaborate with technical and business stakeholders to develop scalable data and knowledge solutions aligned with business requirements.

Required Qualifications
• Strong hands-on experience with AWS Bedrock, Amazon Neptune, and OpenSearch, including vector search and RAG.
• Strong experience with knowledge graphs and ontologies, including RDF, OWL, SKOS, and Turtle.
• Proficiency in Python and SQL.
• Hands-on experience with AWS Glue, Amazon S3, and Apache Iceberg.
• Experience with LangChain, LlamaIndex, and/or Strands Agents.
• Experience implementing Text2SQL solutions.
• Strong data engineering experience combined with LLM and RAG integration experience.

Preferred Qualifications
• Experience in the Life Sciences or Healthcare domain.
• Experience designing and implementing enterprise-scale agentic AI and knowledge management solutions.

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