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# Senior Data Architect

- **Company:** DEPLOY, LLC
- **Location:** Atlanta, GA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Accounting Systems, Artificial Intelligence, Data Architecture, Data Governance, Data Infrastructure, Data Structures, Logic Synthesis of Circuits, Power BI, Reverse Engineering, Apache Spark, Data Layers, Build Management, Data Management, Databricks
- **Published:** May 20, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=6c83e02247ca11c3

## About the Role

Do you have experience in Data modeling?, Required:
Strong data modeling and schema design experience (conceptual, logical, physical)

Experience with Databricks and/or Spark-based data platforms

Demonstrated ability to reverse-engineer undocumented schemas and infer entity relationships

Experience building canonical or enterprise data models in complex, multi-source environments

Semantic layer design experience (ideally with Power BI as the downstream consumer)

Comfortable working with business stakeholders to define data definitions and governance policies

Eager to learn AI tooling

Strongly Preferred:
Experience in regulated industries with complex data environments

Experience with Medallion Architecture (bronze/silver/gold patterns)

Familiarity with enterprise transaction and accounting systems

Experience with modern AI tool sets

Environment

Our client environments are managed with strict security controls and restricted internet access.

You should be comfortable working within enterprise security constraints.

## Description

Meaningful AI helps organizations unlock the value in their data. We design and build AI-driven data platforms, taking clients from raw, undocumented data environments through to canonical models, semantic layers, and analytics-ready infrastructure.

What You'll Do

Design canonical data models for core business domains

Discover and interpret schemas across complex legacy datasets (like Databricks)

Reverse-engineer existing data structures and infer relationships across systems

Establish standardized naming conventions, data definitions, and source-to-canonical mappings

Collaborate with client data teams to understand data structures, calculated fields, and transformation logic

Design semantic layers and data governance frameworks

Provide architectural direction for downstream data models

Advise on ML-ready data products


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