Data Architect

Heaven Hill BrandsLouisville, KY
22hOnsite

About The Position

The Data Architect is an invididual contributor position, responsible for partnering across IT and business teams to define, build, and govern Heaven Hill’s enterprise data architecture. This role designs and executes scalable data models and platforms that enable trusted analytics, operational reporting, and reusable datasets, while ensuring strong data integrity, governance, and a great user experience. The Data Architect will define enterprise-wide data architecture standards and target-state designs to support our EDW modernization to Microsoft Fabric (Warehouse) and Power BI, guiding solution choices, data modeling and integration patterns, and platform conventions to enable scalable, trusted analytics across the business. In partnership with AI Engineering, the Data Architect will define standards for ingesting and curating both structured and unstructured data for tools like Retrieval-Augmented Generation (RAG) and Model Context Protocol (MCP) while working with Security on governed access, so AI solutions are secure, explainable, and used as trusted data. This role is hands-on (medium to high) in the near term, with a focus on creating standards, reviewing designs, and enabling delivery. Through proven success, it will evolve toward broader governance and enablement as adoption matures.

Requirements

  • Bachelor’s degree (Computer Science, Engineering, Information Systems, Data Science, Statistics) or equivalent experience.
  • Minimum 8 years of experience in data architecture, analytics engineering, or data engineering with strong architecture ownership.
  • Strong expertise in enterprise data modeling and analytics design (e.g., dimensional modeling and modern warehouse patterns).
  • Demonstrated ability to standardize semantic models and reporting layers across teams (Power BI semantic modeling preferred).
  • Experience establishing or operating data governance practices (data quality, lineage, access control, and secure data sharing).
  • Ability to translate business goals into technical solutions and drive adoption through influence and formal governance processes.
  • Strong communication and collaboration skills across technical and non-technical audiences.
  • Experience with Microsoft Fabric (Warehouse/OneLake) and Power BI at enterprise scale.
  • Experience with data solutions across on-prem and cloud environments, including connectivity, security/access patterns, and operational considerations.
  • Familiarity partnering with Security and governance tooling such as Microsoft Purview (classification, lineage, access).
  • Hands-on or architecture-level experience with RAG patterns (retrieval design, embeddings/vector search concepts, and evaluation approaches).
  • Familiarity implementing or integrating Model Context Protocol (MCP) or similar tool/data connector patterns for AI applications.
  • Experience designing ingestion and governance for unstructured content alongside structured warehouse data.

Responsibilities

  • Translate cross-functional business needs into scalable enterprise data architecture (models, integration patterns, and reference architectures)
  • Roadmap digital transition so internal and external data sources are useful for self-service analytics and AI tools
  • Set and enforce standards for Microsoft Fabric Warehouse (medallion architecture, workspace strategy, naming conventions, reusable templates)
  • Own Power BI semantic layer and metric governance (certified datasets, shared dimensions, dataset standards, consistent metric definitions)
  • Drive data and trust compliance with Security and governance partners (quality, lineage, access controls, auditability) using Purview and platform controls
  • Align ERP master/reference data definitions with analytics needs in partnership with the Accounting Master Data team
  • Enable delivery by collaborating with Data Engineering on ingestion/transformation and translating architecture into epics/stories and design review guardrails
  • Lead a formal Data Architecture CoP to standardize practices, run design reviews, and manage exceptions
  • Define AI data readiness standards (structured + unstructured ingestion), governed RAG patterns, and MCP-based data/tool access in parntership with AI Engineering; advice Security/AI Center of Excellence on controls. Implementation delivered in partnership with AI Engineering and Security
  • Evaluate 3rd party solutions for Governance, Master Data Management, AI Agents, etc.

Benefits

  • Paid Vacation
  • 11 Paid Holidays
  • Health, Dental & Vision eligibility from day one
  • FSA/HSA
  • 401K match
  • EAP
  • Maternity/Paternity Leave
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