Senior Data & AI Engineer: Semantic Models & LLM Pipelines

RADcube; Carmel (IN); On-site; USD 130,000 - 180,000; Full time

Job summary

RADcube in Carmel, IN is seeking a Senior Data & AI Engineer to design and maintain scalable data models and semantic layers for AI-driven solutions. You will work on text-to-SQL, RAG workflows, and metadata foundations, collaborating with AI engineers and stakeholders to align data with business KPIs.

You will translate business questions into data requirements, document schemas, and ensure governance and quality across data assets, enabling accurate AI-assisted analytics for clients.

Qualifications

• 6+ years of experience in data engineering, analytics engineering, or BI development.
• Strong SQL skills and understanding of relational and dimensional modeling.
• Experience navigating large enterprise schemas (e.g., SAP, Salesforce, MES).
• Hands-on with AWS and/or Azure cloud data platforms and Databricks or Snowflake.

Responsibilities

• Build and maintain data models including dimensional, relational, and lakehouse designs.
• Document unfamiliar schemas with ER diagrams, data dictionaries, and lineage.
• Develop and optimize SQL, transformations, and data pipelines on cloud platforms.
• Create semantic models covering metrics, dimensions, hierarchies, and relationships.

Skills

SQL

Relational modeling

Dimensional modeling

Data modeling

Stakeholder communication

Python data work

LLMs on structured data

Data governance awareness

Cloud platforms knowledge

Tools

AWS

Azure

Databricks

Snowflake

dbt

LookML

Cube

Unity Catalog

Collibra

AWS DataZone

Job description

RADcube in Carmel, IN is seeking a Senior Data & AI Engineer to design and maintain scalable data models and semantic layers for AI-driven solutions. You will work on text-to-SQL, RAG workflows, and metadata foundations, collaborating with AI engineers and stakeholders to align data with business KPIs.

You will translate business questions into data requirements, document schemas, and ensure governance and quality across data assets, enabling accurate AI-assisted analytics for clients.