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# Lead Data Architect

- **Company:** Vsg Business Solutions
- **Location:** Minneapolis, MN, United States
- **Experience:** Expert
- **Salary:** $112,700.0 - $193,200.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Architectural Patterns, Microsoft Azure, Big Data, Cloud Database, Information Systems, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Dataspaces, Data Systems, Data Warehousing, Software Design Patterns, Distributed Data Store, Python (Programming Language), Machine Learning, Operational Data Store, Power BI, Cloud Services, Azure Machine Learning, Data Streaming, Enterprise Data Management, Sql Optimization, Snowflake, Apache Spark, HybridCloud, Microsoft Fabric, Data Lakes, Information Technology, Data Management, Data Pipelines, Databricks
- **Published:** September 26, 2026
- **Apply:** https://www.careerjet.com/jobad/us5a68bd7c3af6200d2b5c7cb38079865e

## About the Role

Bachelor's degree in Computer Science, Information Systems, Engineering, or a
related technical discipline.
10+ years of professional experience in data engineering, data architecture, data
platform engineering, or closely related disciplines.
At least 5 years of experience designing and implementing enterprise-scale
cloud data platforms.
Strong experience with cloud-based data services.
Advanced SQL skills.
Strong Python experience.
Experience with distributed data-processing technologies such as Spark.
Strong knowledge of ETL/ELT architecture and frameworks.
Experience designing modern data warehouse, data lake, or lakehouse
environments.
Strong understanding of enterprise data modeling and architecture patterns.
Experience implementing data governance, data quality, security, and access
control standards.
Experience designing scalable and resilient enterprise data solutions.
Demonstrated technical leadership experience.
Experience mentoring or providing architectural direction to Data Engineers.
Experience working within regulated, security-sensitive, or highly governed
environments.
Highly Desirable Experience
Experience with several of the following would be particularly valuable:
Microsoft Azure data technologies
Databricks
Snowflake
Microsoft Fabric
Power BI
Real-time or streaming data architectures
AI/ML platforms
Enterprise cloud migrations
Large-scale data modernization
AI enablement initiatives
Relevant cloud, data-engineering, architecture, or data-platform certifications are also

## Description

Empowers Staffing is recruiting an experienced Lead Data Architect for a financial
services organization.
This is a senior technical leadership position responsible for defining and advancing
enterprise data architecture while helping modernize a large-scale cloud data
environment.
The successful candidate will establish architecture standards, guide data engineering
teams, design scalable data solutions, strengthen governance and security, and help
prepare the organization's data environment for advanced analytics and AI.
The position requires someone who can operate at the architecture and strategy level
while remaining technically hands-on., Define and evolve enterprise data architecture, standards, models, and design
patterns.
Lead architecture and solution design for modern cloud-based data platforms.
Design scalable environments supporting analytics, reporting, operational data, and
advanced data use cases.
Establish architectural standards for data integration, security, governance, quality,
performance, and reliability.
Provide technical leadership and mentorship to Data Engineers and other technical
professionals.
Serve as a senior escalation resource for complex data-platform and engineering
issues.
Participate in the architecture, development, and review of data pipelines and
integration processes.
Guide ETL/ELT architecture and engineering practices.
Lead modernization of legacy and existing data environments.
Improve platform scalability, resiliency, performance, and operating efficiency.
Partner with technology, analytics, risk, compliance, and business teams to
translate requirements into practical data solutions.
Establish approaches for secure and governed enterprise data access.
Help ensure data solutions meet regulatory, security, privacy, and internal
governance requirements.
Evaluate new technologies and recommend improvements to the organization's
data ecosystem.
Support cloud migration and data-platform transformation initiatives.
Advance organizational readiness for AI, machine learning, advanced analytics,
and intelligent automation.
Help establish architecture that supports both traditional data warehousing and
modern lakehouse approaches.
Provide technical direction throughout solution design, implementation, and
ongoing platform evolution.


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