Architect: Enterprise Data

Mayer Brown LLP•Chicago, IL

1d•$140,000 - $185,000•Hybrid

About The Position

Mayer Brown is an international law firm positioned to represent the world’s major corporations, funds, and financial institutions in their most important and complex transactions and disputes. We are recognized by our clients as strategic partners with deep commercial instincts and a commitment to creatively anticipating their needs and delivering excellence in everything we do.We are a collegial, collaborative firm where highly motivated individuals with an unwavering commitment to excellence receive the opportunity, support, and development they need to grow, thrive, and realize their greatest potential all while supporting the Firm’s client service principles of excellence, strategic partnership, commercial instinct, integrated strengths, innovation, and collaboration across our international firm.If you enjoy working with team members whose defining characteristics are exceptional client service, initiative, professionalism, responsiveness, and adaptability, you may be the person we are seeking to join our Information Technology department in our Chicago office, as an Architect: Enterprise Data. The Architect: Enterprise Data is a critical role within the Global Data and Analytics team, responsible for owning enterprise semantic model architecture with a primary focus on Finance-aligned analytical models. Mayer Brown’s Data and Analytics team plays a central role in ensuring the accuracy and integrity of enterprise data so it can be used to deliver analytical insights that drive the firm forward. The semantic models this role designs and governs serve as a foundational layer for business intelligence, analytics, and increasingly as the trusted source for Copilot, data agents, and AI-driven delivery across the firm. The role requires designing, governing, and evolving a critical, curated set of high-value semantic models that centralize core financial and operational domains and support broad, reusable analytics use cases across the organization.

Requirements

Bachelor’s degree in Information Management, Data Science, Computer Science, or a related discipline.
5-7 years of experience in data engineering, Power BI development, semantic model development, or data architecture with demonstrated expertise in designing and implementing enterprise semantic models, preferably in a legal, professional services, or financial services environment with complex data governance requirements
Experience developing Power BI reports and semantic models for stakeholders for Finance
Proven experience in cloud-based data engineering using Microsoft Azure, Azure Data Factory, SQL Server, and Microsoft Fabric technologies, including hands-on development of ETL/ELT processes, data transformations, and lakehouse architectures
Experience with data modeling and architecture design using tools such as Microsoft Visio, implementing star schema, dimensional modeling, and data warehouse design patterns for business intelligence and analytics solutions
Demonstrated ability to work with cross-functional teams, including data stewards, IT teams, business analysts, and legal professionals to translate business requirements into technical data solutions and documentation
Strong experience architecting and governing semantic models for enterprise analytics
Advanced Power BI experience, including semantic model design and optimization
Deep understanding of data modeling concepts, especially star schema and dimensional modeling
Advanced DAX proficiency for measure authoring, calculation groups, and performance optimization
Experience working with or supporting financial systems (e.g., GL, AP/AR, budgeting, forecasting, financial reporting)
Hands-on experience with Direct Lake mode or modern Lakehouse-backed semantic models
Familiarity with Microsoft Fabric IQ, ontology frameworks, and AI-readiness patterns for semantic layers
Experience with TMDL and/or TMSL for semantic model serialization, source control integration, and automated deployment
Familiarity with Microsoft Purview for data cataloging, lineage, and sensitivity labeling
Proven ability to define and standardize financial metrics and calculations
Experience integrating semantic models with Power BI, Excel, and other analysis tools
Experience implementing CI/CD pipelines for data model promotion, versioning, and governance
Strong collaboration skills with both technical teams and finance/business stakeholder
Proficiency in programming languages including Python, SQL, and PowerShell for data manipulation, automation, and scripting, with experience in version control systems (Git) and collaborative development practices
Deep understanding of data analytics, business intelligence, and data management principles
Strong written and verbal communication skills, with the ability to communicate effectively and professionally at all levels of the firm, including senior leadership, technical teams, and external vendors.
Ability to work in a diverse, cross-functional team environment, effectively supporting the demanding needs of a global law firm.
Proven ability to work under pressure and manage multiple priorities, meeting deadlines in a fast-paced environment with shifting priorities.
Must be a self-starter, demonstrating a high level of initiative in problem-solving, process improvement, and driving data management best practices.
Strong customer service orientation, anticipating stakeholder needs, proactively addressing concerns, and exercising independent judgment.
Exceptional attention to detail and organizational skills, ensuring accuracy in documentation, data integrity, and process adherence across multiple projects.
Maintains confidentiality and exercises discretion.
Ability to present complex data concepts to nontechnical stakeholders, translating technical information into clear, business-friendly insights.
Collaborate effectively across departments and organizational levels, ensuring alignment between business needs, IT capabilities, and governance policies.
Strong analytical and problem-solving skills with a focus on delivering business value through data-driven solutions to enhance reporting, data governance, and decision making.
Deep understanding of data analytics, business intelligence, and data management principles

Nice To Haves

Master’s degree in Information Management, Data Science, Computer Science, or a related discipline.
Industry-recognized certifications (preferred):
Microsoft Certified: Fabric Data Engineer Associate (DP-700)
Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
Preferred experience in multinational environments with exposure to international data privacy regulations (GDPR, CCPA), multi-jurisdictional compliance requirements, and enterprise-scale data governance policies
Experience with version control systems like Git, CI/CD pipelines, infrastructure as code, and DevOps practices for data engineering workflows and automated deployment processes

Responsibilities

Own the architecture, design, and lifecycle of enterprise semantic models, with an emphasis on Finance-aligned data products
Partner closely with Finance, Accounting, and Analytics stakeholders to define, standardize, and maintain financial metrics, KPIs, and calculations
Architect star-schema and dimensional data models optimized for analytical performance and business usability
Design data architecture blueprints using Microsoft Visio and other tools, creating technical specifications for data flows and integration points
Centralize related data domains into a limited number of well-governed semantic models to reduce duplication and promote consistency across reporting
Ensure semantic models support self-service analytics while maintaining metric accuracy, traceability, and governance
Implement and manage Direct Lake mode semantic models where appropriate to balance performance, freshness, and cost
Implement and evolve Microsoft Fabric IQ capabilities — including ontology definitions and semantic annotations — to establish trusted context for Copilot, AI agents, and generative AI-driven analytics delivery
Author and optimize DAX measures and calculations to support complex financial reporting, KPI standardization, and self-service analytics consumption
Enable seamless consumption of models across Power BI, Excel, and other analytical tools
Define and govern enterprise modeling standards, naming conventions, and documentation to support enterprise adoption
Integrate semantic models with Microsoft Purview for data cataloging, lineage tracking, and sensitivity classification to ensure end-to-end governance visibility
Align data model lifecycle management with governance and access control frameworks through CI/CD pipelines, ensuring promotion, versioning, and policy enforcement are automated and auditable
Manage semantic model serialization using TMDL (Tabular Model Definition Language) to enable Git-based source control, code review, and automated deployment
Collaborate with data platform analytics teams to align physical data structures with semantic layer needs
Advise on workspace and capacity governance within Microsoft Fabric to ensure optimal deployment topology, cost management, and performance isolation