Enterprise Data Architect

We are seeking a strategic and technical Enterprise Data Architect to support the evolving needs of the firm’s Master Data Management (MDM) program. This role is responsible for helping to define and operationalize a modern MDM strategy to include supporting the collection & centralization of critical data sources (Data Lakehouse), architecting system integration processes, and managing the data governance framework to ensure data consistency, accuracy, and accessibility across the firm’s environment.

This role combines enterprise data architecture, platform engineering, and governance expertise to deliver measurable business value, improve data reliability and usability, and enable analytics, reporting, and emerging data driven capabilities. The position plays a critical role in aligning data platform design and execution with the firm’s strategic objectives, operational needs, and regulatory expectations common to a professional services environment. It’s not just about secure, clean data;

it’s about enabling better and faster decisions.

Operating with a hands‑on mentality and an ownership mindset, this role partners closely with ingest and curate data from core systems, establish authoritative data domains, and ensure data is consistently modeled, secured, and governed throughout its lifecycle.

The ideal candidate will bring a balance of architecture rigor and engineering pragmatism, with a strong focus on data governance data quality, data platform stewardship. We are looking for a candidate that is passionate about building trusted, enterprise grade data platforms and turning complex data environments into reliable, well governed assets that support informed decision making.

This list of duties and responsibilities is not all inclusive and may be expanded to include other duties and responsibilities as the position and department evolve. Incumbents must be able to perform all essential functions with or without reasonable accommodation.

• Execute the firm’s enterprise data platform strategy by helping to design, develop, and maintain a modern Data Lakehouse that supports trusted analytics, reporting, and operational use cases.
• Define and implement MDM approaches for key enterprise data domains, including authoritative data sources, data models, and lifecycle management.
• Establish and apply enterprise data architecture and governance standards, including data modeling conventions, metadata, data quality controls, lineage, and access management.
• Embed data governance, security, and compliance requirements directly into data platform design and implementation, supporting auditability and risk management expectations in a professional services environment.
• Partner with application owners, analytics teams, and business stakeholders to ingest data from core systems and ensure data is fit for enterprise use.
• Provide hands‑on technical leadership through architectural guidance, solution design, and review of data platform implementations and vendor deliverables.
• Develop reusable data frameworks, patterns, and documentation to promote consistency, efficiency, and long‑term platform sustainability.
• Monitor data platform performance and data quality, identify opportunities for optimization, reliability improvements, and cost efficiency.
• Stay current on data platforms, architecture, and governance trends and recommend practical enhancements aligned with firm priorities.

The requirements listed are representative of the knowledge, skills, and/or abilities required to satisfactorily perform the essential functions of this position. Michael Best will always consider candidates with an equivalent combination of relevant experience and education.

• Bachelor’s degree in Information Systems, Computer Science, Engineering, or a related field, or an equivalent combination of education and relevant work experience.
• Minimum of 7–10 years of progressive experience in data architecture, data engineering, or enterprise data platform roles.
• Demonstrated experience designing and supporting modern data platforms (e.g., Data Lakehouse, analytics platforms, enterprise data…