Data Platform Architect / Data warehouse Architect (Level 5) excels in tracking emerging industry capabilities for modern Enterprise Data Platform (EDP), developing target state Data Platform Architecture, and architecting Data, Analytics, and ML Products that are aligned with the enterprise data strategy, data landscape, data skills, data security, and data sharing needs to support the realization of enterprise Business Strategy outcomes with the following track record.
Roles and Responsibilities:
Data Platform Architect / Data warehouse Architect (Level 5) excels in tracking emerging industry capabilities for modern Data Platforms, developing target state Data Platform Architecture, and architecting Data, Analytics, and ML Products that are aligned with the enterprise data strategy, data landscape, data skills, data security, and data sharing needs to support the realization of enterprise Business Strategy outcomes
Designs, implements, and supports MDHHS data warehouse and analytics platform modernization initiatives. Recommends and leads State of Michigan teams in adopting emerging cloud-based data services, analytical tools, and other modern technologies. Oversees the organizational sustainability of data warehouse and data analytics process improvement. The Data Platform Architect's responsibilities include:
Design and maintain the overall architecture for enterprise data platforms, ensuring scalability, reliability, and alignment with business objectives.
Oversee the implementation of modern data platform components, such as storage, streaming, and orchestration services, and ensure they function cohesively.
Establish governance frameworks for data quality, security, metadata management, and compliance with organizational and regulatory requirements.
Collaborate with engineering, analytics, security, and business teams to translate strategic needs into technical solutions and roadmap initiatives.
Responsible for selection of appropriate hardware, software, tools and system lifecycle techniques for different components of data warehouse architecture including ETL, Metadata, data profiling software, performance monitoring, reporting and analytic tools.
Highly Desired:
Desirable to have demonstrated experience in Supporting the enterprise in ensuring that all the Data Engineering efforts such as POCs, early implementations, and technology refresh of legacy systems etc. are aligned to help the Data Engineering team stay focused on systematically building and maturing the required technical and delivery capabilities
Desirable to have experience in tracking the Architectural adherence of Data Engineering Products and Pipelines to the Enterprise Architecture Standards and Best Practices and supporting the Data Engineering team to systematically enhance their capability maturity in delivering high-quality Data Engineering Products.
Assignment duration: 1 year+ contract dependent on business need
Position location: Lansing, MI (HYBRID: There is NO remote-only option. Wednesdays and Thursdays are required on-site days (non-negotiable))
*Open to local candidates or those willing to relocate BUT they must relocate from day one AND they must come on-site for 2nd round interview. Candidates not willing to do this will not be considered.
Interview process: Virtual and In-person. First round will be virtual, second round will be on-site. Mix of technical and soft skills. For the virtual round it will be a 60-minute Virtual Interview via MS Teams (video required). Candidates should join from a laptop and be prepared to share their screen if requested. A screenshot photo of candidate will be required for any
