Work you'll do

As a Finance Data & AI Manager specializing in Microsoft Azure and Fabric, you'll lead teams that design end-to-end solutions from source integration and OneLake through trusted data products, AI, and Power BI. You will guide architecture from strategy through production.
• Lead engagements or workstreams that define end-to-end Azure and Fabric architectures across integration, OneLake, lakehouse/warehouse, security, AI, and finance consumption
• Guide batch, streaming, mirroring, and orchestration design with Fabric Data Factory, Data Engineering, Spark, Data Warehouse, and Real-Time Intelligence
• Establish governance, lineage, Entra-based access, data quality, observability, service-level objectives, and remediation with Microsoft Purview
• Define reusable finance data products, canonical models, OneLake sharing, APIs, and governed semantic models for planning, close, profitability, treasury, and reporting
• Architect production ML and generative and agentic AI with Fabric Data Science and Azure AI services, MLOps and LLMOps, evaluation, monitoring, and responsible AI
• Manage client relationships, estimates, design reviews, deployment, capacity and cost outcomes; mentor teams and support demonstrations, proposals, and RFP responses
• Agentic Redesign of Finance data and processes such as planning, forecasting, close, profitability, treasury, or reporting

A successful candidate would possess these skills:

? Ability to work independently and collaborate as part of a team

? Ability to translate finance outcomes into clear architecture decisions

? Effective written, verbal, and executive communication skills

? Meticulous attention to detail and quality of work product

? Ability to build and sustain professional relationships

? Ability to lead projects or workstreams

? Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment

? Ability to meet deadlines

? Ability to mentor and provide clear guidance to others

The team

Deloitte's Finance Transformation offering helps finance and global business services leaders navigate an increasingly challenging environment marked by disruptive tech like AI, market uncertainty, and regulatory change, and recognize the opportunity to better serve the enterprise, shareholders, customers, and regulators.

Within the Finance Transformation offering, our Business Finance team drives strategic value through planning, forecasting, and analytics. We design trusted finance data products, modern platforms, and AI-enabled solutions that deliver timely, actionable insights.

Qualifications

Required:
• 6+ years of experience architecting enterprise data, analytics, or AI solutions in a corporate or consulting environment
• 4+ years of experience designing Azure or Fabric solutions across data engineering, lakehouse/warehouse, security, performance, and multi-environment deployment
• 4+ years of experience with finance data and processes such as planning, forecasting, close, profitability, treasury, or reporting
• Bachelor's degree in Computer Science, Data Science, Information Systems, Finance, Accounting, Engineering, Mathematics, or a related field
• Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
• Limited immigration sponsorship may be available.

Preferred:
• Experience with OneLake, Lakehouse, Data Warehouse, Data Factory, Data Engineering, Real-Time Intelligence, Direct Lake, Power BI, and Purview
• Experience with data quality, observability, lineage, testing, CI/CD, infrastructure as code, and capacity/cost optimization
• Experience deploying ML, retrieval-augmented generation, or agentic AI with Azure AI or Fabric Data Science and responsible AI controls
• Experience integrating SAP, Oracle, Workday, Anaplan, or OneStream and building governed Power BI semantic models, DAX measures, and reports
• Microsoft certification in Azure architecture, Fabric, or Power BI; or a master's degree in a related field
• 2+ years of experience supporting pre-sales, proposals, RFP responses, and mentoring data and AI delivery teams