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Data Warehouse Architect

Stafford GrayLansing, Michigan🇺🇸United StatesPosted 3 Sept 2026

Quick Overview

Seniority
Mid Senior
Employment type
Temporary/Casual
Work mode
Hybrid
Location
Lansing, Michigan, United States
Posted
6 hours ago
SQLTableauDatabricksJavaPower BIPython

Job Description

The Data Platform Architect / Data Warehouse Architect (Level 5) tracks emerging industry capabilities for modern Enterprise Data Platforms (EDP), develops target-state Data Platform Architecture, and architects Data, Analytics, and ML Products aligned with enterprise data strategy, data landscape, data skills, data security, and data sharing needs — supporting the realization of enterprise business strategy outcomes.

Required Skills (Must haves):

  1. Minimum 5 years experience leading Data Architects and working with Enterprise Architects to develop Data Landscape, Data Strategy, and Data Architectural approaches using an industry-standard architecture framework (e.g., TOGAF 9, FEAF, DODAF) to align data landscape with business, application, and technology landscapes in support of a data-driven business strategy.
  2. Minimum 5 years experience developing Reference Architectures and an Architecture Patterns Library, and conducting Architectural Reviews to identify and manage architectural exceptions, ensuring architectural integrity of an Enterprise Data Platform in a large enterprise.
  3. Minimum 3 years experience driving the RFP process for selecting Data Platform technologies, partnering with vendors to co-develop innovative EDP capabilities, driving EDP innovation, and promoting a data-driven decision-making culture through Communities of Practice.
  4. BS in Computer Science, Data Science, Information Systems, or a related field — required.

Most Preferred Skills:

  • Experience with Data Lake, Delta Lake, EDP, Data Warehousing, and Databricks

Key Programming Languages: SQL, Python, R, Java

Other Technologies/Concepts/Frameworks: TOGAF, Data Lake, Delta Lake, NoSQL DB, GraphDB, EDP, Data Warehousing, Data Marts, Databricks, Operational Data Stores, Power BI, Tableau

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