Designing and maintaining the technical architecture of the firm's Data Lakehouse environment is the core of this role, ensuring data is structured, integrated, and available for business intelligence, reporting, analytics, and AI initiatives. The Data Architect works closely with the Database Platform Lead, business stakeholders, and technology teams to translate requirements into scalable, secure, and maintainable data solutions.
Responsibilities
Design and maintain the technical architecture of the Firm’s Data Lakehouse environment, ensuring solutions are scalable, secure, maintainable, and aligned with established technology standards
Work closely with the Database Platform Lead and business stakeholders to understand business processes, data requirements, reporting needs, and integration requirements and translate those requirements into technical data solutions
Identify and evaluate data sources required to support business intelligence, reporting, analytics, AI, and other approved data use cases
Design data structures, data flows, integration approaches, and data mappings to ensure data is appropriately organized and available for downstream use
Configure and maintain data connectors and integrations between the Data Lakehouse and Firm applications, databases, and other approved data sources
Work with the Database Platform Lead and source system owners to understand source data structures, identify data dependencies and limitations, and resolve data integration issues
Establish and apply appropriate data modeling, transformation, integration, performance, security, and data quality practices within the Data Lakehouse environment
Work closely with the Business Intelligence Developer, AI Solutions Engineer, Senior Software Developers, and other technology resources to ensure data structures and integrations effectively support downstream solutions
Participate in the evaluation, design, testing, implementation, and optimization of Data Lakehouse capabilities and integrations
Provide technical guidance regarding data architecture, integration patterns, data structures, and platform capabilities and help ensure implementations conform to approved architectural standards
Document data architecture, data mappings, data flows, source systems, dependencies, integration designs, and other technical information necessary to support the Data Lakehouse throughout its lifecycle
Evaluate emerging data platform, cloud, analytics, automation, and AI technologies and recommend appropriate architectural approaches and improvements to the Firm’s Data Lakehouse environment
Keep abreast of emerging data architecture practices, technologies, and industry trends and apply appropriate developments to improve the Firm’s ability to leverage enterprise data
Requirements
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Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field, or equivalent relevant experience
Minimum of five years of experience in data architecture, data engineering, data integration, data warehousing, or a related technical discipline
Experience with Microsoft Azure and Databricks
Demonstrated experience designing and implementing enterprise data solutions, including data structures, data models, data integrations, and data pipelines
Strong proficiency in SQL and experience working with relational databases, data warehouses, and enterprise data platforms
Strong understanding of data modeling concepts, including relational and dimensional modeling, data structures, relationships, keys, and data dependencies
Hands-on experience with ETL/ELT processes, data integration patterns, data transformation, data mapping, and data validation
Experience identifying, analyzing, and integrating data from multiple enterprise applications, databases, APIs, or other data sources
Experience working with cloud-based data platforms and modern data architecture concepts, including data lake, data warehouse, or Lakehouse architectures
Experience designing and implementing secure, scalable, and maintainable data solutions that support business intelligence, reporting, analytics, or other downstream applications
Demonstrated ability to translate business and reporting requirements into technical data architecture and integration solutions
Understanding of data quality, data security, access control, data lineage, and governance principles as they apply to enterprise data solutions
Strong analytical, troubleshooting, problem-solving, documentation, and communication skills, with the ability to explain technical data concepts to both technical and non-technical audiences
Ability to work effectively with business stakeholders, application owners, developers, architects, vendors, and other technology resources
Nice to have:
Experience working with a cloud-based data Lakehouse, data warehouse, enterprise analytics, or comparable data platform, including hands-on experience with Entegrata or similar technologies
Experience with Microsoft Fabric, Azure Data Factory, Azure Data Lake Storage, or related cloud data technologies
Experience with Power BI, Power BI semantic models, or other enterprise business intelligence and reporting platforms
Experience with data integration technologies and methods, including APIs, REST/JSON, database connectivity, file-based integrations, and data connectors
Experience with Python, PySpark, or other programming languages used for data engineering and automation
Experience with data pipeline orchestration, scheduling, incremental loading, error handling, monitoring, and deployment
Familiarity with enterprise data architecture, dimensional modeling, data quality, data governance, metadata management, and data lineage concepts
Experience integrating data from enterprise applications, particularly financial, time and billing, HR, CRM, document management, and matter management systems commonly used by law firms
Experience supporting data platforms, analytics, or data solutions in a law firm, professional services organization, or other confidentiality-sensitive or highly regulated environment
Experience with Azure DevOps, Git, CI/CD, or other tools supporting source control and deployment of data solutions
Experience supporting analytics, artificial intelligence, machine learning, or other advanced data use cases
Relevant Microsoft Azure, Databricks, data engineering, or cloud certifications
About the Company
McGuireWoods, one of the world’s leading law firms, has provided legal solutions to corporate, individual and nonprofit clients since 1834. Diversity and inclusion are essential to how they do business, informing how they recruit, retain and promote lawyers and staff to serve clients.
