Senior Director, Partner Insights
Listed on 2026-08-02
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IT/Tech
Business Intelligence, Data Analyst
What You’ll Do
The Senior Director of Partner Insights leads analytics for Avalara’s partner ecosystem — referral and technology partnerships — owning the metrics, models, and executive-facing narrative that inform how the company invests in and manages partner channels. This is a data and analytics leadership role first: you’ll build and run a high-performing team that turns partner and BD funnel data into decisions, and you’ll be the analytical backbone for partner-related board and executive reporting.
You’ll sit inside the Data & Analytics organization, embedded in the Partner domain — with a mandate to define, defend, and evolve the metrics partner leadership runs on (referral/tech partner performance, commission economics, BD funnel conversion), consistent with the definitional standards Data & Analytics owns company-wide.
#LI-Remote
What Your Responsibilities Will Be Team & Function Leadership- Own and grow the Partner Insights team, setting the analytics roadmap and quality bar for all partner-facing reporting and analysis.
- Establish Partner Insights as the authoritative source for partner performance metrics and definitions, in alignment with company-wide metric standards owned by Data & Analytics.
- Help drive the team’s adoption of AI-enabled analytics and self-service BI — including semantic layer design that makes partner metrics consistent, governed, and directly queryable by business stakeholders and AI tools alike.
- Build and maintain the financial models and business cases that inform partner strategy, investment decisions, and executive/board-level positioning.
- Run the BD funnel analysis — lead generation through deal close — using Salesforce and warehouse data to surface revenue optimization opportunities for the partner and sales organizations.
- Partner with Revenue Operations on channel/technology partner performance deep-dives and commission structure analysis, providing the analytical foundation for commission model design.
- Own the preparation and quality of partner-related content for monthly business reviews and board decks; partner with CRO/CFO on positioning.
- Translate partner and BD funnel performance into a clear, decision-ready narrative for executive and investor audiences.
- Partner with Finance on annual planning, budgeting, and target-setting for the partner organization.
- Work with Marketing on top-of-funnel drivers, campaign performance, and lead qualification/conversion metrics as they relate to partner-sourced pipeline.
- Collaborate with Data Engineering and Analytics Engineering to ensure partner data pipelines and semantic models meet the team’s analytical needs.
- 12+ years of experience in analytics, FP&A, or business intelligence leadership, ideally in SaaS or technology-platform businesses at scale (750+ employees); partner/channel or BD-adjacent experience a strong plus.
- Track record building and leading data/analytics teams that operate as strategic partners to executive stakeholders, not just a reporting function.
- Deep fluency in translating complex data into financial models and business cases that hold up under executive and board scrutiny.
- Experience partnering with Data Engineering/Analytics Engineering teams — comfortable operating in a modern warehouse/BI stack, not just consuming finished dashboards.
- Experience advancing semantic layer and self-service BI initiatives, and a point of view on where AI fits into analytics workflows and decision support.
- Proven experience managing global, cross-functional stakeholders (GTM, Finance, Revenue Operations) and driving alignment without formal authority over those functions.
- Strong people leadership and team-building track record.
- MBA a plus, not required.
- Advanced SQL required;
Python fluency strongly preferred. - Experience with Salesforce and Snowflake (or equivalent cloud data warehouse).
- Experience with next-generation BI tools such as Hex or Omni preferred.
- Familiarity with Fivetran or similar ELT/pipeline tooling — enough to collaborate effectively with data engineering, not…
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