Role Summary
We are seeking a Senior Data Architect to provide an independent thirdparty perspective on an ongoing enterprise Data Modernization program The role focuses on architecture assurance risk mitigation and acceleration of platform adoption ensuring alignment with enterprise scale best practices and longterm strategic goals
The architect will work independently with client stakeholders and multiple vendor teams validating decisions challenging assumptions and guiding the program toward a scalable secure and futureready lakehouse architecture on Databricks
Key Responsibilities
1 Architecture Advisory Independent Review
Provide objective thirdparty evaluation of the current data platform architecture design choices and implementation approach
Review and validate lakehouse architecture including ingestion transformation storage and consumption layers
Identify gaps design risks and antipatterns across the platform
Recommend alternative approaches and tradeoffs aligned to enterprise standards
2 Data Modernization Strategy Alignment
Assess alignment to modern data platform paradigms Lakehouse ELT Medallion architecture
Validate architectural decisions around
o Data ingestion patterns batch streaming unstructured data integration
o Data modeling and transformation strategies
o Analytics and AIML readiness of the platform
Ensure consistency with enterprisescale governance security and performance requirements
3 Risk Identification Derisking
Proactively identify technical architectural and operational risks impacting delivery timelines and scalability
Conduct design reviews and provide mitigation strategies and decision frameworks
Flag dependencies constraints and potential longterm impacts of current design choices
Support leadership with architecture risk summaries and decision recommendations
4 MultiVendor Stakeholder Engagement
Work independently with
o Customer architects and SMEs
o Internal delivery teams
o Thirdparty vendors
Facilitate architecture discussions workshops and governance reviews
Act as a neutral technical authority to resolve architectural conflicts and drive consensus
5 Best Practices Governance
Define and enforce architecture standards design patterns and guardrails
Ensure adoption of
o Databricks and Spark best practices
o Data governance frameworks including cataloging access control and auditing
o Performance cost optimization and scalability standards
Provide guidance on DataOps DevOps practices
