Senior Business Intelligence Engineer

You’ll design, build, and maintain Microsoft Fabric artifacts - Lakehouses, Warehouses, Semantic Models, Pipelines, Notebooks, and Reports - and advise Power BI report developers on dimensional modeling and tabular design best practices. What You Will Be Doing

• Extend and build Microsoft Fabric data solutions using DAX, tables, relationships, and roles in Semantic Models, along with Lakehouse and Warehouse components
• Maintain existing data solutions, including current SSIS and SSRS environments, and design new ones from the ground up, including dimensional data warehouse models
• Lead application deployments, upgrades, and patch planning
• Collaborate with the Data Analytics team to identify and implement AI-assisted BI development in Microsoft Fabric
• Create and deliver end-user training and documentation, and provide second-line and level 3 support for assigned data solutions, including resolution of escalated incidents and problem management
• Ensure alignment between the data analytics platform and business requirements
• Mentor junior developers
• Track emerging technology trends and make recommendations to the Manager, Data Analytics Services
• Participate in daily scrum meetings and in software licensing and support agreement discussions
• Help evaluate the business relevance and requirements of prospective projects
• Bring professionalism and a solution-oriented approach to every interaction, communicating clearly and courteously with internal departments, clients, and vendors
• Demonstrates a strong commitment to professionalism, delivering high-quality service, and maintaining a positive, solution-oriented (“can-do”) approach. Effectively supports internal departments, external clients, and vendors through clear, courteous communication via electronic correspondence, telephone, and in-person interactions., #L1-Hybrid This job description is intended to describe the general nature and level of the work being performed by employees in the position. It is not intended to be a complete list of all responsibilities, duties, and skills for positions. The firm reserves the right at all times, in its sole discretion, to add or subtract duties and responsibilities, as it deems necessary.

• Hands-on experience with Microsoft Fabric (Lakehouse, Warehouse, Data Factory, Real-Time Intelligence)
• Advanced T-SQL skills, including dimensional modeling and a disciplined coding style for readability and supportability
• Experience designing, building, and managing scalable ETL/ELT pipelines, ideally including Azure Data Factory pipelines across sources such as SQL databases, SharePoint, and Excel, plus working knowledge of supporting Azure services (Key Vault, Logic Apps, Storage Accounts)
• Experience with DevOps version control and CI/CD for BI assets, including configuring CI/CD pipelines that support Azure Data Factory
• Expert knowledge of data warehouse architecture, data design patterns, and data transformation best practices at medium-to-large data volumes
• Intermediate to advanced knowledge of DAX
• Proficiency in Power BI: report development, semantic modeling, and deployment pipelines
• Hands-on experience implementing Microsoft Fabric Semantic Models (or Tabular models) in a medium-to-large enterprise setting
• Manage and maintain Power BI/Fabric gateways, including installation, configuration, access, and connectivity troubleshooting
• Working knowledge of Python or PySpark for notebook-based transformations (R or Python for predictive analytics and visualization is a plus)
• Strong problem-solving skills and persistence in building performant solutions at scale (hundreds of millions of records)
• Experience supporting a 24x7 production environment
• Strong analytical skills, including advanced research involving interpretation of data from varied sources
• Ability to translate business questions and requirements into reports, views, and SQL queries
• Intellectually curious and self-directed; takes initiative researching and troubleshooting before escalating
• Strong collaboration and communication skills - works effectively with users and technical staff in team environments, translating technical concepts for non-technical audiences
• Ability to manage multiple projects, shifting priorities, and deadlines independently

• Open to technological change as generative AI becomes more integrated into the firm’s practice; willing to adopt new tools and adapt workflows to support efficiency and innovation Required Experience

• 1+ year of hands-on experience with at least two Microsoft Fabric item types (Lakehouse, Warehouse, Pipelines, or Semantic Models)
• 2+ years of DAX experience
• 3-6 years of experience in data analysis and data warehousing, with deep specialization in one or more areas above
• A plus: experience with legal financial data models, + Bachelor’s degree in computer science or related field; or equivalent work experience, + Hands-on experience with Microsoft Fabric (Lakehouse, Warehouse, Data Factory, Real-Time Intelligence)
• Advanced T-SQL skills, including dimensional modeling and a disciplined coding style for readability and supportability
• Experience designing, building, and managing scalable ETL/ELT pipelines, ideally including Azure Data Factory pipelines across sources such as SQL databases, SharePoint, and Excel, plus working knowledge of supporting Azure services (Key Vault, Logic Apps, Storage Accounts)
• Experience with DevOps version control and CI/CD for BI assets, including configuring CI/CD pipelines that support Azure Data Factory
• Expert knowledge of data warehouse architecture, data design patterns, and data transformation best practices at medium-to-large data volumes
• Intermediate to advanced knowledge of DAX
• Proficiency in Power BI: report development, semantic modeling, and deployment pipelines
• Hands-on experience implementing Microsoft Fabric Semantic Models (or Tabular models) in a medium-to-large enterprise setting
• Manage and maintain Power BI/Fabric gateways, including installation, configuration, access, and connectivity troubleshooting
• Working knowledge of Python or PySpark for notebook-based transformations (R or Python for predictive analytics and visualization is a plus)
• Strong problem-solving skills and persistence in building performant solutions at scale (hundreds of millions of records)
• Experience supporting a 24x7 production environment
• Strong analytical skills, including advanced research involving interpretation of data from varied sources
• Ability to translate business questions and requirements into reports, views, and SQL queries
• Intellectually curious and self-directed; takes initiative researching and troubleshooting before escalating
• Strong collaboration and communication skills - works effectively with users and technical staff in team environments, translating technical concepts for non-technical audiences
• Ability to manage multiple projects, shifting priorities, and deadlines independently
• Open to technological change as generative AI becomes more integrated into the firm’s practice; willing to adopt new tools and adapt workflows to support efficiency and innovation

• The hiring range for this position is $150,000 - $185,300 annually, with final compensation based on experience, qualifications and internal equity.
• This position is eligible for a Hybrid Schedule
• Medical, dental, and vision insurance
• 401(k) with company match and profit-sharing options
• Paid time off and holidays

WilmerHale is a leading, full-service international law firm with 1,000 lawyers located throughout 12 offices in the United States and Europe. Our lawyers work at the intersection of government, technology and business, and we remain committed to our guiding principles of providing quality, excellent legal and client services; developing diversity among our lawyers and staff and cultivating an environment that promotes an ambitious spirit, collaboration and collegiality by drawing on the extraordinary talents and dynamic experience of our lawyers. Our goal is to reflect the diversity of our clients and the communities in which we practice.