Data warehouse engineer Jobs in USA

Job Summary:

The Data Warehouse Architect (Level 5) role involves designing, implementing, and supporting modern enterprise data platforms and analytics solutions for the State of Michigan. This position focuses on developing scalable, reliable data architectures aligned with business strategies, driving innovation in data technologies, and enforcing data governance and security standards. The architect will lead modernization initiatives, collaborate across teams, and oversee vendor selection and procurement processes to support data-driven decision-making within a hybrid work environment.

Responsibilities:

• Design and maintain enterprise data platform architecture ensuring scalability and alignment with business objectives.
• Lead modernization initiatives of data warehouse and analytics platforms.
• Recommend and guide adoption of emerging cloud-based data services and analytical tools.
• Oversee organizational sustainability of data warehouse and analytics process improvements.
• Establish governance frameworks for data quality, security, metadata management, and regulatory compliance.
• Collaborate with engineering, analytics, security, and business teams to translate strategic needs into technical roadmaps and solutions.
• Drive RFP processes and vendor partnerships to select and co-develop innovative data platform technologies.
• Architect data services portfolios and products aligned with industry best practices and enterprise capabilities.
• Ensure adherence to data governance and security standards within data engineering products and pipelines.
• Manage architectural reviews and exceptions to maintain enterprise data platform integrity.
• Conduct proofs of concept and lead technology innovation initiatives within the enterprise.
• Support operationalization of data engineering environments and delivery of data/analytics/ML pipelines.

Required Skills & Certifications:

• Bachelor's degree in Computer Science, Data Science, Information Systems, or related field.
• Minimum 5 years leading data architecture and collaborating with enterprise architects using frameworks such as TOGAF, FEAF, or DODAF.
• Minimum 5 years developing reference architectures, architecture pattern libraries, and conducting architectural reviews.
• Minimum 3 years experience driving RFP processes and vendor partnerships for data platform technology selection.
• Proven expertise in enterprise data platform architecture, data governance, and data security standards implementation.
• Experience with data platform full technology stack, including cloud service providers and enterprise data platforms.
• Strong knowledge of data warehousing, data lakes, delta lakes, and modern data engineering methodologies.

Preferred Skills & Certifications:

• Experience with Databricks, NoSQL databases, GraphDB, operational data stores, and data marts.
• Proficiency in programming languages such as SQL, Python, R, and Java.
• Familiarity with business intelligence tools like Power BI and Tableau.
• Knowledge of enterprise architecture frameworks and data engineering delivery methodologies.
• Experience promoting data-driven culture through communities of practice and innovation programs.

Special Considerations:

• Hybrid work schedule with mandatory on-site presence Wednesdays and Thursdays; no remote-only option.
• Candidates must be willing to relocate immediately if not local and attend on-site second-round interviews.
• Approximately 20% travel required, including driving between Lansing and University of Michigan campus.
• Candidates must provide two professional references and valid Right to Represent documentation.
• Strict resume submission guidelines: 4-5 pages, legal first and last name only; withdrawn candidates cannot be replaced.
• Virtual first-round interview with video and screen sharing via MS Teams; photo and vendor presence required.

Scheduling:

• Full-time, 40 hours per week.
• Hybrid schedule requiring on-site work Wednesdays and Thursdays.
• Contract duration approximately 1 year with possibility of extension based on business needs.
• Interview process includes virtual and in-person rounds.