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 ------------------------------------------------------------------------------------------------------
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