Data Warehouse Architect

About the Role

Our Client is seeking a seasoned Data Warehouse Architect to lead the design and implementation of enterprise-wide data solutions. In this role you will collaborate with Enterprise Architects, business stakeholders, and technology vendors to shape the data landscape that supports strategic decision-making. You will be responsible for creating reference architectures, establishing architecture standards, and guiding the development of a modern Enterprise Data Platform. The position operates in a hybrid environment with on-site collaboration days, ensuring alignment between technical delivery and business objectives.

Key Responsibilities

• Lead the development of the enterprise data landscape, data strategy, and architectural approaches using frameworks such as TOGAF, FEAF, or DODAF.
• Design and document reference architectures, architecture pattern libraries, and conduct architectural reviews to maintain platform integrity.
• Partner with vendors to evaluate, select, and integrate data platform technologies through RFP processes and co-development initiatives.
• Define and govern data lake, delta lake, and data warehousing solutions, including implementation on platforms like Databricks.
• Establish and nurture Communities of Practice to promote data-driven decision making across the organization.
• Provide technical guidance and mentorship to data engineering and analytics teams throughout the project lifecycle.
• Ensure compliance with enterprise data governance, security, and quality standards.
• Collaborate with business units to translate business requirements into scalable data models and pipelines.

Required Skills & Experience

• Minimum 5 years of experience leading data architecture initiatives and working closely with Enterprise Architects.
• At least 5 years designing reference architectures, architecture pattern libraries, and conducting architectural reviews in large enterprises.
• Minimum 3 years driving RFP processes, vendor negotiations, and co-development of Enterprise Data Platform capabilities.
• Strong understanding of data lake, delta lake, data warehousing concepts, and modern data platforms such as Databricks.
• Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field.
• Proven ability to align data solutions with business, application, and technology strategies.
• Excellent communication and stakeholder management skills, with experience presenting technical concepts to non-technical audiences.

Tools & Technologies

• Architecture frameworks: TOGAF, FEAF, DODAF.
• Data platforms: Databricks, Delta Lake, enterprise data lake solutions.
• Data modeling and warehousing tools: SQL, dimensional modeling, ETL/ELT processes.
• Cloud environments (e.g., Azure, AWS, GCP) for data platform deployment.
• Collaboration and documentation tools: Confluence, SharePoint, Visio.
• Version control and CI/CD tools such as Git and Azure DevOps for architecture artifacts.

Work Schedule & Duration

• Hybrid schedule with mandatory on-site presence on Wednesdays and Thursdays.
• Contract duration of 1 year with the possibility of extension based on business needs.
• Full-time engagement (40 hours per week) with occasional travel to the client site in Lansing.

Interview Process

The interview process consists of two stages. The first round is a 60-minute virtual interview via Teams, focusing on technical expertise and problem-solving abilities; candidates must join from a laptop and be prepared to share their screen. The second round is an on-site interview at the client’s Lansing office, evaluating both technical depth and soft-skill fit. A photo screenshot of the candidate is required for identity verification, and a vendor representative will be present at the start of the virtual interview.

Position Details

• Employment Type: Contract
• Duration: Approximately 12 months (with potential for extension)
• Work Authorization: Must be authorized to work in the United States