Senior Databricks Data Engineer Jobs in Lansing, MI

Position Data Platform Architect / Data Warehouse Architect

Client Name Michigan Department of Health and Human Services (DHHS)

Requisition 165331

Location Lansing, MI

Duration 1+ years

Due Date 09/10/2026

C2C Possible Yes. Rate depends on experience

Interview Method 1st round - webcam, 2nd round - Onsite

NOTE: Open to local candidates or those willing to relocate BUT they must relocate from day one Hybrid Work Schedule (non-negotiable). There is NO remote-only option. Wednesdays and Thursdays are required on-site days (non-negotiable. We can accept H1b, H4, TN and other valid work visas for IT. However we cannot accept OPT or CPT visas at this time.

Our client seeks a Data Platform Architect / Data Warehouse Architect who excels in tracking emerging industry capabilities for modern Enterprise Data Platforms (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

Tasks:

• 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.

• 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.
• 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 years' experience in driving RFP process of selecting Data Platform Technologies
• 5+ years - Experience in developing Enterprise Data Technology Strategies, articulating the use of the Data Engineering Delivery Methodologies, building the Data Engineering Standards & Best Practices
• Demonstrated expertise in driving innovation related to modern data technology platforms through conducting Proofs of Concepts, Codathon, and Co-development with technology vendors, to fully comprehend the business capabilities feasible from emerging technologies to design effective Proofs of Concepts and lead the execution of POCs in the enterprise to support technology decision making in the enterprise.
• Experience in the full technology stack within an Enterprise Data Platform offering of any CSP to help an enterprise set up the initial fully functioning instance of an EDP containing all the required tools to enable the Data Engineering team in conducting Proofs of Concepts and operationalizing the Product Environment for the delivery of Data Engineering products including Data/Analytics/ML pipelines.
• Demonstrated experience in driving the procurement process (RFI/RFP etc.) in a large enterprise to select the Cloud Service Provider vendor for building and hosting the EDP.
• Demonstrated experience in architecting Data Services Portfolio and Data Products that are aligned with the industry best practices and internal data engineering capabilities.
• Demonstrated expertise in baking in the Data Governance standards and best practices into the development and usage of the Data Engineering Products including the Data/Analytics/ML pipelines and Data/Analytics/ML Products.
• Demonstrated experience in enforcing the adherence to the implementation of Data Security Standards and Best Practices into the Data Engineering Products including Data/Analytics/ML Products and Data Pipelines to minimize data security vulnerabilities.
• BS in Computer Science / Data Science / Information Systems or a related Computer Science degree
• Experience with Data Lake, Delta Lake, EDP, Data Warehousing, and Databricks
• Experience in tracking the Architectural adherence of Data Engineering Products and Pipelines to the Enterprise Architecture Standards