Data Platform / Data Warehouse Architect

Key Programming Languages: SQL, Python, R, Java Other Technologies, Concepts and Frameworks: TOGAF, Data Lake, Delta Lake, NoSQL DB, GraphDB, EDP, Data Warehousing, Data Marts, Databricks, Operational Data Stores, Power BI, Tableau

1. Minimum 5 years experience in leading Data Architects and working with Enterprise Architects to develop Data Landscape, Data Strategy, Data Architectural approaches using any industry standard Architecture framework such as TOGAF 9, FEAF, DODAF etc. to align data landscape with business, application and technology landscapes of an enterprise to support the implementation of data-driven business strategy.
2. Minimum of 5 years experience in developing Reference Architectures, Architecture Patterns Library, conducting Architectural Reviews to identify exceptions, and managing the architectural exceptions to ensure architectural integrity of Enterprise Data Platform in a large enterprise.
3. Minimum of 3 years experience in driving RFP process of selecting Data Platform Technologies, partnering with vendors to codevelop innovative EDP capabilities, driving EDP innovation, and promoting data-driven decision-making culture in the enterprise through Communities of Practice etc.
4. Must have a BS in Computer Science / Data Science / Information Systems or a related CS degree

Most Preferred Skills -Experience with Data Lake, Delta Lake, EDP, Data Warehousing, and Databricks, 1. Enterprise Data Architecture: 5+ years in Data Platform/Data Warehouse Architecture, Enterprise Data Strategy, Target-State Architecture, and TOGAF/FEAF/DoDAF.

1. Modern Data & Cloud Technologies: Strong experience with Enterprise Data Platform (EDP), Databricks, Data Lake, Delta Lake, Data Warehousing, Data Marts, ODS, NoSQL, GraphDB, and cloud platforms.
2. Programming & Analytics: Proficiency in SQL, Python, R, Java, plus Power BI and Tableau; experience architecting Data/Analytics/ML pipelines and products.
3. Governance, Security & Data Products: Experience with Data Governance, Data Quality, Metadata Management, Data Security, Compliance, and architecting Data Services/Data Products.
4. Innovation & Enterprise Delivery: Experience leading POCs/Codathons, vendor co-development, RFI/RFP & Cloud Service Provider selection, and implementing enterprise data platform modernization, including ETL, data profiling, performance monitoring, reporting, and analytics.

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.

Assignment Duration: 1yr+ contract dependent on business need

Hybrid Work Schedule (non-negotiable): 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.

Travel Requirement: Will sometimes drive from downtown Lansing to University of Michigan Campus. 20% travel. Candidates MUST be willing to do this.

References: Candidates must provide 2 Professional references.

Candidates MUST meet all these requirements from the beginning