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About the Role
We are looking for a dynamic Manager of Finance to serve as the primary data authority for the Wealth Advisory (WA) Finance team. This is a high-impact individual contributor role that sits at the intersection of data engineering, financial analysis, and business intelligence. The Manager will live in the granular details—databases, raw data sets, and complex data pipelines—and transform that depth into actionable insights that power the financial analysis performed across the broader WA Finance team. The role reports to the Director of Finance, Wealth Advisory, and provides critical data infrastructure and analytical support to the Senior Manager and the full team. Finance is heavily involved in financial modeling, product and offer profitability analyses, and reporting in support of WA and its business functions including Sales, Strategy, and Offer Management. This Manager will be the engine behind that work—owning the data layer so that the rest of the team can perform at the highest level.
Responsibilities
- Own the team’s data infrastructure—design, build, and maintain scalable databases, data pipelines, and automated workflows that enable the WA Finance team to access timely, accurate, and granular business data
- Extract and transform complex data across all WA data domains—including billing, client assets, holdings, strategy, client transactions, expense and revenue allocations, household demographic data, account data, and flows data—to surface insights that drive strategic financial decisions
- Enable superior financial analysis across the WA Finance team by delivering clean, structured, and well-documented data outputs that team members can rely on for forecasting, modeling, and reporting
- Build scalable, automated data processes using Python, SQL, and other coding languages, and leverage AI tools to expand the team’s analytical reach and efficiency
- Collaborate with WA Finance team members, finance, data and technology partners to understand evolving data needs and ensure the team’s data capabilities grow with the business
- Innovate by continuously improving data processes, introducing new tools and techniques, and applying AI-enabled approaches to solve complex data challenges at scale
- Develop deep knowledge of how Wealth Advisory generates revenue, manages expenses, and serves clients—becoming the team’s go-to expert on the data that explains how the business operates
- Deliver ad-hoc data analyses and custom data pulls in support of business cases, forecasts, P&L performance reviews, and other analytical needs across the team
Requirements
- 5+ years of progressive experience in financial analysis, data analytics, or a related field with demonstrated depth in data management and extraction
- Expert proficiency in Python and SQL, including writing complex queries, building data pipelines, and automating analytical processes
- Hands-on experience working with relational databases and large, granular data sets—comfortable navigating raw data environments to identify and resolve data quality issues
- Demonstrated ability to use AI tools and techniques to design and implement scaled data processes that increase team efficiency and analytical capacity
- Experience with financial or business data domains such as billing, client assets, transactions, revenue and expense allocations, or similar—ideally within financial services or wealth management
- Proven track record as a high-performing individual contributor who takes ownership of complex analytical workstreams and delivers results with minimal oversight
- Strong communication skills with the ability to translate complex data findings into clear, actionable outputs that non-technical colleagues can use effectively
- Familiarity with analytical and financial systems
Skills
- Python
- SQL
- AI tools
- Data management
- Data extraction
- Relational databases
- Financial analysis
- Data analytics
- Analytical and financial systems
Experience Level
- 5+ years of progressive experience
Education Level
- Bachelor’s degree in Finance, Accounting, Computer Science, Data Science, Economics, or a related field