Hybrid Enterprise Data & AI Architect

HTC Global Services, Inc.; Grand Rapids (MI); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid and Workplace flexibility

Well-defined career development plan

Rewards & Recognition program

L&D focuses on upskilling

Hands-on experience on Emerging Tech &

Job summary

HTC Global Services is seeking an experienced Enterprise Data Architect to lead design, governance, and deployment of scalable data platforms across cloud and on-prem environments.

The role emphasizes data modeling, governance, data integration, and AI/ML enablement, collaborating with stakeholders, data engineers, analytics teams, and solution architects to ensure scalable, secure, and high-performing solutions.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or a 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.

Responsibilities

• Define and maintain enterprise data architecture principles, standards, and best practices.
• Design scalable, secure, and resilient data platforms supporting analytics, AI/ML, and operational workloads.
• Create conceptual, logical, and physical data models.
• Develop enterprise data roadmaps aligned with business strategy.

Skills

Communication

Stakeholder management

Leadership

Mentoring

Analytical thinking

Problem solving

Education

Bachelor's or Master's in CS/IS/Data Science

Tools

Snowflake

Databricks

Azure Synapse

Microsoft Fabric

AWS Redshift

Google BigQuery

dbt

Informatica

Talend

Kafka

SQL Server

Oracle

MongoDB

Microsoft Purview

Collibra

Alation

Unity Catalog

Python

SQL

PySpark

Scala

Git

GitHub Actions

CI/CD

Terraform

Job description

HTC Global Services is seeking an experienced Enterprise Data Architect to lead design, governance, and deployment of scalable data platforms across cloud and on-prem environments.

The role emphasizes data modeling, governance, data integration, and AI/ML enablement, collaborating with stakeholders, data engineers, analytics teams, and solution architects to ensure scalable, secure, and high-performing solutions.