CertifID is a company dedicated to enhancing security and fighting fraud in the real estate sector. They are seeking a Senior Business Analyst to serve as the analytical engine behind business operations, focusing on financial and operational reporting, data analysis, and cross-functional planning processes.
Responsibilities:
- Partner with the Director of FP&A and senior leadership to develop financial and operational reporting, forecasts, and performance analyses that drive real decisions - not just decks
- Own the data access layer for the Business, from Finance to all GTM teams. You'll write SQL queries against our data warehouse (Supabase/PostgreSQL), build and maintain analyses in Hex and Metabase, and develop the reporting infrastructure that gives Finance and business leaders visibility into what's actually happening in the business
- Translate business questions into data requirements, and then go get the data yourself. You won't be handing tickets to the data team for every pull; you'll be a self-sufficient operator who knows when to go directly to the warehouse and when to collaborate with data engineering on something more complex
- Build and maintain dashboards, KPIs, and operational scorecards that give leadership real-time visibility into business performance. Own these end-to-end, from data model to presentation layer
- Support cross-functional planning processes, including budgeting, forecasting, and long-range planning - synthesizing inputs from across the business and building the models that inform how we allocate resources
- Act as a bridge between business stakeholders and the data team, helping scope analytical projects correctly and ensuring the output actually answers the business question
- Be the analytical backbone for our GTM teams. You'll work closely with Sales, Marketing, and Customer Success to move beyond scorecards and reporting - your job is to shorten the distance between data and decision, helping leaders quickly understand not just what's happening in the business but why it's happening and what they should do next
- Use AI tools as a core part of your workflow - for accelerating analysis, automating recurring work, drafting and sense-checking outputs, and identifying patterns at a scale that wouldn't be practical manually. Help raise the bar for how Finance and Operations teams use AI across the organization
Requirements:
- 5-7 years of experience in FP&A, business operations, strategy, analytics, or a related role where you were working with real data, not just summaries handed to you by someone else
- Genuine, demonstrated AI fluency. This means you have changed how you actually do your work because of AI tools - not that you've taken a course or used ChatGPT occasionally. We want to hear specifically how AI shows up in your day-to-day: what you've automated, what you've accelerated, what you've built. Prompt engineering, LLM-assisted analysis, and workflow automation experience are all relevant
- SQL is required. You need to be able to write queries from scratch, navigate a data warehouse independently, and troubleshoot when results look off. Comfort with Supabase/PostgreSQL and MotherDuck specifically or cloud-based warehouses generally (Snowflake, BigQuery, DuckDB) is a strong plus
- Experience with notebook-based analytics tools - Hex, Metabase, Mode, Observable, Databricks, or similar. This is how we work, and familiarity with this type of environment matters
- Strong finance and analytical skills - you understand how the three financial statements flow, you're intimately familiar with SaaS KPIs, you can build a forecast from scratch, and you know how to pressure-test the assumptions behind it
- Excellent communication skills - you can write a tight one-pager for a CFO and also sit in a technical scoping conversation with a data engineer and be credible in both rooms
- A business-first mindset. You lead with the question, not the tool. The 'so what' matters more to you than the methodology
- Bachelor's degree in Finance, Economics, Business, Statistics, Computer Science, or a related field
- Python proficiency is a plus, particularly for data manipulation and analysis (pandas, etc.). Not required, but meaningful
- MBA or advanced degree is a plus but not a substitute for hands-on technical experience