🚨 Data & AI Architect / Enterprise Data Architect – Grand Rapids, MI

Job Title: Data & AI Architect / Enterprise Data Architect
Location: Grand Rapids, MI
Work Arrangement: Hybrid
Employment Type: Direct Hire

Position Overview

We are seeking an experienced Data & AI Architect / Enterprise Data Architect to lead the design, implementation, and governance of enterprise-scale data platforms.

The ideal candidate will have 10+ years of experience in Data Engineering, Data Warehousing, or Data Architecture, including 5+ years designing enterprise cloud data platforms.

The candidate should have strong expertise across Snowflake, Databricks, Microsoft Fabric, Azure/AWS/Google Cloud Platform, data modeling, data governance, data integration, and AI/ML enablement.

Key Responsibilities

Enterprise Data Architecture

• Define enterprise data architecture principles, standards, and best practices.
• Design scalable, secure, resilient data platforms supporting analytics, AI/ML, and operational workloads.
• Create conceptual, logical, and physical data models.
• Develop enterprise data architecture roadmaps aligned with business objectives.
• Lead architecture reviews and provide technical direction across multiple teams.

Cloud Data Platform Architecture

• Architect modern cloud data platforms using Snowflake, Databricks, Microsoft Fabric, Azure Synapse, AWS Redshift, and Google BigQuery.
• Design Data Lakehouse, Data Warehouse, and Data Mesh architectures.
• Build scalable data ingestion, transformation, and serving layers.
• Support enterprise cloud migration and data modernization initiatives.

Data Integration

• Design batch, streaming, CDC, and API-based integration solutions.
• Architect ETL/ELT pipelines using:
  • Azure Data Factory
  • Apache Airflow
  • dbt
  • Informatica
  • Talend
  • Fivetran
  • Kafka
• Establish reusable enterprise integration patterns and frameworks.

Data Modeling

• Design star schema, snowflake schema, normalized, and dimensional data models.
• Develop enterprise data marts and domain-specific data models.
• Optimize data models for reporting, analytics, and AI workloads.
• Define master data and reference data models.

Data Governance

• Establish enterprise data governance standards and frameworks.
• Define metadata management strategies.
• Implement data lineage and data catalog solutions.
• Define data quality frameworks, standards, and KPIs.
• Support regulatory and compliance requirements.

AI/ML & Advanced Analytics

• Design data foundations supporting Machine Learning and Generative AI solutions.
• Enable real-time analytics and predictive modeling.
• Support feature stores and semantic layers.
• Partner with Data Scientists and ML Engineers to enable production AI/ML solutions.

Performance & Optimization

• Optimize cloud data platform performance and cost.
• Design partitioning, clustering, indexing, and caching strategies.
• Improve scalability, reliability, and overall platform efficiency.

Stakeholder Collaboration

• Work with business stakeholders to translate requirements into scalable data solutions.
• Partner with engineering, analytics, and architecture teams.
• Provide technical leadership throughout solution design and implementation.
• Mentor data architects, engineers, and developers.

Required Qualifications

• Bachelor''s or Master''s degree in Computer Science, Information Systems, Data Science, or related field.
• 10+ years of experience in Data Engineering, Data Warehousing, or Data Architecture.
• 5+ years of experience designing enterprise cloud data platforms.
• Strong understanding of enterprise architecture principles.
• Strong experience designing and implementing enterprise-scale data platforms.
• Excellent communication and stakeholder-management skills.

Required Technical Skills

Cloud Platforms:

• Microsoft Azure
• AWS
• Google Cloud Platform

Data Platforms:

• Snowflake
• Databricks
• Microsoft Fabric
• Azure Synapse Analytics
• BigQuery
• Redshift

Programming:

• Python
• SQL
• PySpark
• Scala preferred

Data Integration:

• Azure Data Factory
• Apache Airflow
• dbt
• Informatica
• Talend
• Kafka
• Fivetran

Databases:

• SQL Server
• Oracle
• PostgreSQL
• MongoDB
• Cosmos DB

Data Governance:

• Microsoft Purview
• Collibra
• Alation
• Unity Catalog

DevOps / Infrastructure:

• Git
• Azure DevOps
• GitHub Actions
• CI/CD
• Terraform

Preferred Qualifications

• Experience with enterprise-scale cloud migration projects.
• Experience with data modernization initiatives.
• Strong Data Lakehouse implementation experience.
• Experience with Data Mesh architectures.
• Experience supporting AI/ML platform architecture.
• Real-time streaming architecture experience.
• Multi-cloud architecture experience.
• Experience in Insurance, Healthcare, Financial Services, Retail, or Manufacturing.
• Experience designing complex enterprise data integrations.

What We''re Looking For

The ideal candidate is a strategic, hands-on Enterprise Data Architect who can define architecture strategy while working closely with engineering and business teams.

Candidates with strong experience in Snowflake, Databricks, Microsoft Fabric, cloud architecture, data modeling, governance, integration, and AI/ML enablement are highly preferred.