Company Description
United Hub Digital (UHD) is a nearshore IT consulting firm helping mid and large US enterprise clients accelerate their data and technology initiatives. Headquartered in Greenville, SC, with a delivery hub in Brazil, we embed directly into client teams as a trusted execution partner across data analytics, software development, UI/UX, and project management. We hold ourselves to the same standards of accountability and delivery quality our clients expect from their own teams.
About the Role
We are looking for a Senior Analytics Engineer to help one of our enterprise clients unlock the value of their data for AI-driven use cases. The goal focus for this role is to 'make the data AI-ready': well-structured, semantically rich, documented, and governed.
Your primary output is a clean, well-documented, and semantically meaningful data environment that downstream AI workloads can reason over reliably.
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What You Will Do
Semantic Modeling
* Design and build semantic layers that translate raw ERP tables into business-meaningful domains (finance, procurement, supply chain, etc.)
* Define and enforce naming conventions, metric definitions, and business logic in a shared, governed layer
* Work with Databricks semantic layer to expose curated datasets for AI and analytics consumption
Data Documentation and Context
* Produce column-level documentation, data dictionaries, and business glossaries inside Unity Catalog
* Establish lineage tracing from source system tables through to consumption-ready datasets
* Collaborate with source systems stakeholders to capture domain knowledge and translate it into structured metadata
AI Readiness
* Structure data to support LLM-based and ML workloads, including RAG pipelines and structured querying
* Identify and address data quality gaps that would undermine AI model reliability
* Define thematic data domains and organize datasets to give AI systems the right context and scope
Governance and Quality
* Implement data quality rules and freshness monitors using Databricks tooling
* Tag sensitive fields and support data access tier definitions within Unity Catalog
* Own documentation standards and ensure the catalog remains accurate as data evolves
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Qualifications
Required
* 5+ years in analytics engineering, data architecture, or a closely related discipline
* Hands-on Databricks expertise: Unity Catalog, Delta Lake, cluster configuration, and query optimization
* Experience with semantic modeling tools, ideally dbt (dbt Core or dbt Cloud)
* Strong SQL and a solid understanding of data modeling patterns (star schema, medallion architecture, etc.)
* Ability to read and interpret unfamiliar data models quickly, including ERP-sourced data structures
* Experience writing technical documentation that non-technical stakeholders can act on
Nice to Have
* Exposure to Databricks AI/BI, Genie, or Vector Search
* Experience supporting ML or LLM-based downstream use cases
* Background in data mesh or domain-oriented data architecture