Womble Bond Dickinson (US) LLP seeks a Data Scientist Engineer to design, build, and maintain a modern, enterprise-grade business intelligence platform and analytics capabilities using Microsoft technologies, leveraging AI and data science/business intelligence tools to provide data-driven insights and automate reporting.
Requirements
- 3+ years of experience in data science, data analysis or data engineering using Microsoft technologies, preferably within legal and/or professional services industries.
- Strong working knowledge of Microsoft SQL Server BI and Data Science Tools such as T-SQL, Python/R, PowerBI, SSRS/SSAS, DAX.
- Hands-on experience with Microsoft Fabric and Microsoft’s OneLake architecture.
- Proficiency with ETL tools including Azure Data Factory, Synapse, Fabric, third-party APIs / system integration.
- Ability to learn and leverage existing and emerging AI technologies.
- Demonstrated experience in dimensional modeling and enterprise data warehouse design (Kimball).
- Proficiency with Git and Azure DevOps for collaborative development and deployment.
Responsibilities
- Design and build scalable enterprise business intelligence systems and analytics capabilities for lawyers and staff.
- Develop and maintain dimensionally modeled data warehouses to support reporting and advanced analytics across various operational functions.
- Lead innovative AI-driven approaches to automate workflows and promote data integrity and integration across systems.
- Synthesize and analyze data for reporting (including financial reporting) for complex questions and business problems.
- Collaborate with software/data engineers, analysts, and legal operations stakeholders to define data needs and build structured, governed solutions.
- Participate in data architecture planning and contribute to the firm's overall modernization strategy.
Other
- Bachelor’s Degree or advanced degree, preferably in Computer Science, Statistics or related field.
- Understanding of data governance, compliance, and security requirements in a legal context.
- Experience documenting data models, source mappings, ETL flows.
- Understanding of data security best practices (Security+ or higher certifications desirable).
