Senior Data & AI Engineer
radcubeCarmel, IN
About the role
RADcube is hiring aSenior Data & AI Engineerin Carmel, Indiana(onsite). The role focuses on data modeling, semantic layers, and metadata foundations so AI systems can answer questions accurately, including text-to-SQL and RAG-style workflows, alongside client discovery and stakeholder alignment.
Responsibilities:
- Build and maintaindata modelsincluding dimensional, relational, and lakehouse designs that align with team standards.
- Investigate and documentunfamiliar or legacy schemasby producing ER diagrams, data dictionaries, join paths, and lineage.
- Develop and optimizeSQL, transformations, and data pipelineson cloud data platforms.
- Convert raw tables intobusiness-facing semantic modelscovering metrics, dimensions, hierarchies, and relationships.
- Write and enrichschema metadata and descriptionsto support improved performance forLLM text-to-SQLand generative BI accuracy.
- Partner with AI engineers onRAG pipelines, agent tools, and prompt design when the system relies on structured data.
- Test and evaluateAI-generated queriesfor correctness, including contributions to test sets and guardrails.
- Participate inclient discoveryto understand business processes, KPIs, and reporting requirements.
- Translate business questions into data requirements and validatemetric definitionswith stakeholders.
- Communicate data findings clearly to both technical and non-technical audiences.
- Applydata quality checks, naming standards, and documentation practices.
- Follow relevantgovernance and compliancerequirements (GxP, HIPAA) where applicable.
- Review peers’ work and support junior engineers when needed.
- Requirements6+ yearsof experience in data engineering, analytics engineering, or BI development.
- StrongSQLskills and a solid understanding ofrelational and dimensional modeling .Proven ability to learn and navigate large enterprise schemas (for example, SAP, Salesforce, MES, or similar).Hands‑on experience withAWS(Redshift, Glue, Athena, S3) and/orAzure(Synapse, Fabric, Data Factory), plus
- DatabricksorSnowflake .Proficiency inPythonfor data work.
- Practical exposure toLLMs on structured data, including text-to-SQL, semantic layers, or AI‑assisted analytics.
- Good business sense and comfort discussing KPIs and processes with stakeholders.
Technologies
SQL, Python, AWS (Redshift, Glue, Athena, S3), Azure (Synapse, Fabric, Data Factory), Databricks, Snowflake, SAP, Salesforce, MES, LLMs, text‑to‑SQL, RAG, LangChain, LangGraph, Bedrock Agents, MCP, Unity Catalog, Collibra, AWS DataZone, dbt, Cube, dbt Semantic Layer, LookML, vector databases, knowledge graphs, agentic frameworks. What You Bring (Nice‑to‑Have) Experience with pharma, life sciences, manufacturing and quality, or healthcare data. Experience withdbtor semantic layer tooling such asCube , dbt Semantic Layer, orLookML .Familiarity with vector databases, knowledge graphs, or agentic frameworks (LangChain/LangGraph, Bedrock Agents, MCP).Experience with data catalog tools such asUnity Catalog , Collibra, orAWS DataZone .AWS, Azure, or Databricks certifications.
What Success Looks Like:
- (First 6 Months)
- Semantic models and metadata delivered for at least oneacceleratororclient use case .Measurable improvement inAI-generated query accuracyon datasets you own.
- Schema documentation that enables other team members to adopt and use it.
- Stakeholder confidence that you can understand both their data and their business context.
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JOB OVERVIEW
Experience level
Lead
Location
Carmel, IN
Occupation
Data Warehousing Specialists
Industry
Computer Systems Design Services
Posted
yesterday
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