GenAI Data Engineer — GraphRAG & ETL for Clients

Concept Reply US

Illinois

On-site

USD 90,000 - 110,000

Full time

10 days ago
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Job summary

Concept Reply US in Illinois is seeking a Data Engineer to design and build data pipelines, implement graph database models, and develop GraphRAG pipelines powering GenAI applications for client projects.

You will collaborate with data scientists and engineers, gather requirements from stakeholders, and translate business needs into scalable data solutions while working in a consulting engagement and delivering results for clients.

Qualifications

  • Bachelor's degree required.
  • U.S. citizen or Green Card holder.
  • At least 3 years of professional experience in data engineering or related field.
  • Experience with Python.
  • Experience with AWS or Azure cloud platforms.
  • Experience developing ETL pipelines and familiarity with ETL frameworks.
  • Experience with Databricks and/or Snowflake.
  • Experience with graph databases (e.g. Neo4j).
  • Hands-on experience with GenAI/LLM projects, including RAG and GraphRAG.
  • Direct client-facing experience.

Responsibilities

  • Design, build, and maintain data pipelines and ETL workflows.
  • Build and maintain graph database models supporting downstream applications.
  • Design and implement RAG/GraphRAG pipelines for generative AI apps.
  • Collaborate with data scientists and engineers to enhance data/AI solutions.
  • Engage with client stakeholders to gather requirements and translate business needs into technical solutions.
  • Work with a small cross-functional delivery team.

Skills

Python
GenAI/LLM
ETL pipelines
GraphRAG
Client-facing
AWS/Azure

Education

Bachelor's degree

Tools

Databricks
Snowflake
Neo4j

Job description

Concept Reply US in Illinois is seeking a Data Engineer to design and build data pipelines, implement graph database models, and develop GraphRAG pipelines powering GenAI applications for client projects.

You will collaborate with data scientists and engineers, gather requirements from stakeholders, and translate business needs into scalable data solutions while working in a consulting engagement and delivering results for clients.

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