FacilityOS

Data Analyst, Revenue Operations

FacilityOS · North York, Ontario, Canada · CA$85K–CA$95K/yr

Facilities Services · 51-200 employees

Yesterday
Remote Mid (2-5 yrs) Full-time Canada
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About the role

You will build and maintain semantic models, reporting, and data pipelines within Microsoft Fabric to support revenue operations. Additionally, you will perform deep-dive analysis to drive business decisions and ensure data integrity across the GTM stack.

What they look for

SQL Power BI Data modeling DAX Star schema design Microsoft Fabric Python Salesforce Data pipelines ETL Data integrity B2B SaaS Revenue operations Semantic modeling Data analysis Reporting

Requirements

The role requires 2–4 years of experience in an analytics or BI role with strong proficiency in SQL, Power BI, and Python. Candidates should have experience with cloud-based data pipelines and a solid understanding of the Salesforce data model.

Benefits

Comprehensive health coverage Hybrid work environment Opportunity for advancement and growth Catered events Snacks and drinks Birthday and life celebrations Two annual parties

Full description

About FacilityOS

FacilityOS is a fast-growing company redefining how facilities operate—bringing safety, security, and daily operations into one unified platform used by organizations around the world.

As we continue to scale globally, we’re building a team of driven, curious people who want to make an impact. You’ll be part of a dynamic, collaborative culture where individuals are trusted to take ownership, solve meaningful problems, and grow in their careers. Our team comes together in-office twice a week to connect, collaborate, and build momentum.

If you’re looking to do your best work alongside a great team in a high-growth environment, FacilityOS is the place to build your career.

About the role

Revenue Operations at FacilityOS owns the data layer behind how we go to market and how we build that that layer out on Microsoft Fabric and Power BI, sourced primarily from Salesforce and our GTM stack.

We are hiring a Data Analyst to own the models and reporting that sit on top of it. This is not a dashboard-maintenance role. You will build the semantic models, write the transformation logic, and be the person the GTM leaders and CRO come to when a number doesn't reconcile.

The role suits someone who has spent two to four years doing real analytics work and wants ownership of a data platform rather than a queue of report requests.

What you'll own

  • Semantic models and reporting. Build and maintain Power BI semantic models and reports covering pipeline, bookings, forecast accuracy, conversion, retention, and customer health. Own the definitions, not just the visuals.
  • Data pipelines in Microsoft Fabric. Build and maintain pipelines and notebooks bringing Salesforce and GTM system data into the lakehouse. Own transformation logic, refresh schedules, and data quality checks.
  • Analysis that changes decisions. Quarterly pipeline and coverage analysis, segmentation and territory work, win/loss and cohort analysis, and ad hoc investigation into why a metric moved. Bring a recommendation, not just a chart.
  • Data integrity across the GTM stack. Reconcile Salesforce against downstream systems, find and fix the breaks, and flag the process problems causing them.
  • Documentation. Metric definitions, model lineage, and runbooks that let someone else pick up your work.

What we're looking for

Required

  • 2–4 years in an analytics, BI, or data analyst role, ideally supporting a B2B SaaS revenue or GTM function
  • Strong SQL — joins, window functions, CTEs, query tuning
  • Hands-on Power BI: data modelling, DAX, star schema design, performance optimization
  • Experience building or maintaining data pipelines in a cloud platform. Microsoft Fabric is what we run; Synapse, Databricks, Snowflake, or BigQuery experience translates
  • Python for data work — transformation, API pulls, automation
  • Working knowledge of the Salesforce data model (objects, relationships, reporting quirks)
  • Able to take an ambiguous business question, decide what analysis actually answers it, and present the result to leaders without hand-holding

Nice to have

  • dbt or an equivalent transformation framework
  • Experience with Gainsight, Gong, SalesLoft, Clay, ZoomInfo, or HubSpot
  • Exposure to SaaS revenue metrics — ARR, NRR, pipeline coverage, CAC payback
  • Git and a habit of version-controlling analytical work

How we work

You will often be the most technical person in most rooms you're in. That means explaining your work clearly, pushing back when a request is the wrong question, and being direct about what the data does and doesn't support.

Why work at FacilityOS?

We work hard and play hard and we do both with passion and respect for one another. Our company promotes a fast-paced, fun, friendly, and highly collaborative work environment that provides:

🩺Comprehensive health coverage

🏠A Hybrid work environment

💡Opportunity for advancement and growth

🍕 Catered Events, Snacks, Drinks – You won’t go Hungry!

🥳 Birthday and Life Celebrations

🎉 Two annual parties in a year

FacilityOS Commitment

We believe that a diverse team is the key to innovation and growth. We are an equal opportunity employer that value diversity at our company and encourage all candidates to apply. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

FacilityOS will accommodate individuals with disabilities through each stage of the recruitment and selection process. Please advise us of any needs when your interview is booked, and we will do our best to meet your needs.

Please note that all candidates must be legally eligible to work in the location in which you applied.

Background and Reference Checks

Any offer of employment may be conditional upon full background checks including a criminal record check, a credit check and employment and educational verifications. A reference check will also be conducted.

We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications. These tools assist the recruitment team but do not replace human judgment. All advancement and hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us or click here.

FacilityOS thanks all candidates for their interest, however only those selected to continue in the process will be contacted.