Company DescriptionUnited 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 RoleWe 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.What You Will DoSemantic ModelingDesign 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 layerWork with Databricks semantic layer to expose curated datasets for AI and analytics consumptionData Documentation and ContextProduce column-level documentation, data dictionaries, and business glossaries inside Unity CatalogEstablish lineage tracing from source system tables through to consumption-ready datasetsCollaborate with source systems stakeholders to capture domain knowledge and translate it into structured metadataAI ReadinessStructure data to support LLM-based and ML workloads, including RAG pipelines and structured queryingIdentify and address data quality gaps that would undermine AI model reliabilityDefine thematic data domains and organize datasets to give AI systems the right context and scopeGovernance and QualityImplement data quality rules and freshness monitors using Databricks toolingTag sensitive fields and support data access tier definitions within Unity CatalogOwn documentation standards and ensure the catalog remains accurate as data evolvesQualificationsRequired5+ years in analytics engineering, data architecture, or a closely related disciplineHands-on Databricks expertise : Unity Catalog, Delta Lake, cluster configuration, and query optimizationExperience 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 structuresExperience writing technical documentation that non-technical stakeholders can act onNice to HaveExposure to Databricks AI / BI, Genie, or Vector SearchExperience supporting ML or LLM-based downstream use casesBackground in data mesh or domain-oriented data architecture
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