Senior Data Analyst
Macabacus Senior Data Analyst
About Macabacus:
Macabacus is the leading productivity and brand compliance solution for finance, banking, and consulting teams. Trusted by the world’s top firms, Macabacus accelerates financial modeling, enforces brand consistency, and eliminates costly errors—powering the daily workflows of the most demanding professionals.
About the Role
We're hiring a Senior Data Analyst to be the driving expert behind our data function, building the analytics foundation behind marketing, sales, product usage, and adoption. You'll turn cross-system data into insights that drive decisions from daily operations to leadership.
This is a hands-on role, working from priorities set with leadership, you build the foundation and deliver the insights yourself. You'll partner with a data engineering contractor who takes on the heavier pipeline builds and offers technical direction, while you own the day-to-day, analysis, and the decisions they inform.
The data function, end to end
Macabacus is the leading productivity and brand compliance solution for finance, banking, and consulting teams. Trusted by the world’s top firms, Macabacus accelerates financial modeling, enforces brand consistency, and eliminates costly errors—powering the daily workflows of the most demanding professionals.
About the Role
We're hiring a Senior Data Analyst to be the driving expert behind our data function, building the analytics foundation behind marketing, sales, product usage, and adoption. You'll turn cross-system data into insights that drive decisions from daily operations to leadership.
This is a hands-on role, working from priorities set with leadership, you build the foundation and deliver the insights yourself. You'll partner with a data engineering contractor who takes on the heavier pipeline builds and offers technical direction, while you own the day-to-day, analysis, and the decisions they inform.
Responsibilities
- Seasoned data/analytics background: a stint as the first, only, or lead data person at a B2B SaaS startup or scale-up ($5M–$50M ARR). You've built or leveled up a data function before.
- Expert SQL and data modeling: comfortable making messy, imperfect data trustworthy.
- GTM systems fluency: Salesforce, marketing automation (HubSpot, Marketo, or similar), and product analytics (Amplitude, Mixpanel, Pendo, or similar). You understand how a lead becomes revenue and where the data breaks along the way.
- Strong BI craftsmanship: advanced Tableau (or equivalent) with a track record of dashboards executives actually use.
- Modern data stack fluency: cloud warehouses (Snowflake, BigQuery, Redshift), ELT tools (Fivetran or similar), and dbt. You can operate and extend an existing stack yourself and know when a problem needs a specialist.
- Polished communication: you've presented to senior leadership and built board-ready materials, and can translate analysis into "here's what this means and what we should do."
- AI fluency, not just familiarity: you use AI tools (Claude, ChatGPT, Copilot) daily in your analytics work, can point to concrete wins and limits, build reusable workflows (CLAUDE.md/AGENTS.md, agentic tools like Claude Code), and factor AI into build-vs-buy decisions.
- Builder's judgment: pragmatic build-vs-buy-vs-outsource calls, and comfort with ambiguity and limited resources.
Requirements
What You'll DoThe data function, end to end
- Establish data quality and definition standards and build a foundation that scales with the company.
- Hands-on with the technical side of the stack — transformations, light pipeline changes, and monitoring.
- Partner with a dedicated data engineering contractor (who built our infrastructure) for direction, review, and muscle on heavier projects.
- Build the reporting backbone for marketing and sales: lead flow, stage conversion, pipeline creation and velocity, campaign performance, win/loss patterns.
- Work directly in Salesforce and our marketing automation platform, understand how the data is generated, and fix quality issues at the source, not downstream.
- Stand up reporting on activation, feature adoption, engagement, and the signals that precede expansion or churn.
- Connect usage data to revenue so we see the full customer picture.
- Build and maintain the recurring metrics package for leadership, including board deck materials.
- Numbers that reconcile, definitions that hold up under scrutiny, and narrative-quality presentation — clear takeaways, not chart dumps.
- Build trusted relationships with marketing, sales, product, CX, and finance leaders.
- Understand their goals well enough to anticipate needs, push back on requests that won't answer the real question, and bring leadership insights and recommendations they didn't ask for.
- As a team of one, default to AI-assisted approaches in your own workflow, analysis, SQL, documentation, QA, and in how you evaluate tooling.
- Contribute to how the broader company works with data using AI, making insights more self-serve so you're not the bottleneck.
- Year one centerpiece: a governed semantic layer — trusted definitions and models — that our BI modernization (Tableau Next) and AI-assisted self-serve analytics will sit on.
Benefits
- Finance or fintech SaaS experience
- Python for analysis or automation
- RevOps or GTM operations experience
- Experience defining SaaS metrics (ARR movements, NRR, CAC, LTV, funnel conversion) alongside finance