Data Architect

About the role

Count on us. Our "we-care" culture is more than just a motto; it's a promise. From day one, we prioritize your growth, well-being, and success. You can count on us to support your career journey and help you achieve your professional goals. Join us.

What makes us different? On the surface, we’re one of the nation’s largest audit, tax, consulting, and wealth management firms. But dig a little deeper, and you’ll see what makes us different: we’re a relatively jerk‑free firm (hey, nobody ‘s perfect) with a world‑class culture, consistent recognition as one of Fortune Magazine’s “100 Best Companies to Work For,” and an endless array of opportunities. At Plante Moran, diversity, equity and inclusion means that all staff members have equitable and fair opportunities to succeed, in an inclusive environment, with their individual, unique identities.

Plante Moran enjoys a “Workplace for Your Day” model which, simply put, means we strive for flexibility and balance while staying true to our principally in‑person model. We believe that face‑to‑face interactions are paramount for individual and collective development, but also encourage individuals to work with their supervisor and team to determine their optimal working environment each day. Plante Moran is committed to a diverse workplace. We strive to create a culture where each person feels accepted and valued. We believe that each person’s ultimate potential begins with first acknowledging their inherent dignity. When we can recognize — and celebrate — our many human differences, we’re able to create a workplace where all staff feel a sense of belonging and an opportunity to succeed. This allows us to attract and retain the best talent, serve clients through diverse thinking, and better represent and support the various communities in which we live and work.

Responsibilities

• Partner with business stakeholders, technology teams, and leadership to understand objectives, define business and data challenges, and align on practical data and analytics solutions.
• Lead discovery and solution design efforts, including defining requirements, risks, dependencies, success criteria, target-state architecture, data flows, integration approaches, and implementation roadmaps.
• Design scalable, secure, and governed enterprise data architectures using Microsoft Fabric, Azure Data Services, Databricks, Power BI, and related modern data platform technologies.
• Establish and reinforce architecture standards, Medallion Architecture patterns, development practices, data modeling approaches, CI/CD processes, testing, observability, and operational support expectations.
• Provide technical leadership across multiple concurrent initiatives, translating architecture designs into executable delivery plans and guiding teams through design, build, testing, deployment, and handoff.
• Evaluate technical tradeoffs related to scalability, performance, maintainability, cost, security, governance, and long-term supportability while ensuring alignment with enterprise standards.
• Serve as a trusted advisor and escalation point for complex solution decisions, helping stakeholders navigate ambiguity, balance competing priorities, and reach consensus on the path forward.
• Mentor and supervise a small team of data engineers while modeling accountability, collaboration, continuous improvement, and responsible use of AI-assisted productivity tools.

Qualifications

• Bachelor's degree in Software Engineering, Computer Science, Data Science, or related area required.
• 5-8 years of experience in data architecture, data engineering, analytics engineering, business intelligence, or related technical roles.
• Proven experience designing and delivering enterprise-scale data and analytics solutions from discovery through implementation and production support.
• Strong hands-on experience with Microsoft Fabric, including Lakehouse, Data Engineering, Data Factory, OneLake, and semantic model concepts.
• Experience designing modern lakehouse, warehouse, and data integration architectures using Microsoft Fabric, Azure Data Services, Databricks,