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Juniper Square is a leading operations platform for private markets, serving 2,300+ GPs with $300B+ under administration. The company unifies technology, data, and fund administration services, and is now embedding AI across workflows through JunieAI. Founded in 2014, backed by $350M+ in funding, and 1,000+ employees strong, Juniper Square operates across 27 US states, 2 Canadian provinces, India, Luxembourg, and England.
You will own the revenue analytics infrastructure that powers Juniper Square's business. This role produces the single source of truth for ARR and related metrics consumed by Sales, Finance, Fund Administration, and leadership teams.
Key responsibilities:
**Transformation & Data Modeling**: Own dbt models for revenue and customer data sourced from CRM (Salesforce), CPQ, billing, and ERP (NetSuite) systems. Model the complete chain from quote to order to provisioning to invoice to recognized revenue at entity and service grain. Migrate reporting-level data generation from Salesforce into the warehouse for broader system consumption.
**Semantic Layer & Metric Definitions**: Define and govern certified metrics (ARR, CARR, backlog) and their dimensions. Write definitions precise enough for both people and AI agents to reason over consistently, backed by documentation, tests, and lineage. Reconcile metrics with NetSuite and Finance close to ensure numbers tie out.
**Requirements Translation**: Translate business questions from Sales, Finance, Fund Administration, and leadership into technical requirements for Data Engineering. Work with the Lead Business Systems Analyst and Integrations Engineers to ensure the commercial model and source data are reportable from the start.
**AI-Assisted Reporting**: Build an AI-assisted reporting layer on top of governed semantic definitions so questions asked through tools like Claude return certified answers. Build self-serve dashboards for revenue, operations, and leadership. Stand up measurement for the Lead-to-Cash program.
**Governance & Controls**: Apply access controls, data classification, and change management suited to financial and customer data in SOX, SOC 1, and SOC 2 scope.
Success milestones: own core revenue dbt models and publish draft ARR/CARR/backlog definitions within 90 days; establish a certified semantic layer for revenue metrics within 6 months; achieve one number of record for each revenue metric across Finance, Sales, and leadership with AI-assisted reporting live within 12 months.
**Requirements**
- 5+ years in analytics engineering, data engineering, or business intelligence, including at least 2 years owning dbt models in production
- Expert SQL: window functions, CTEs, performance tuning, and ability to work through legacy queries
- Hands-on dbt experience across models, tests, documentation, incremental models, and CI
- Experience with a semantic layer tool (dbt Semantic Layer/MetricFlow, LookML, Cube, or similar)
- Strong understanding of recurring revenue metrics (ARR, CARR, bookings, backlog, churn) and how they tie to billing and revenue recognition
- Practical data modeling skills: dimensional modeling, slowly changing dimensions, and explicit grain
- Experience working with Salesforce and NetSuite data
- Experience with a cloud data warehouse (Redshift, Snowflake, BigQuery, or similar)
- Regular use of AI coding and data tools (e.g., Claude) in your own workflow
- Comfort working directly with US-based Finance and business stakeholders, with a few hours of overlap with US time zones
**Preferred Qualifications**
- Python for transformation logic, automation, or API-based extraction
- Experience with BI tools such as Looker, Tableau, Power BI, or Sigma
- Exposure to fund administration, private markets, or financial services
- Experience building AI-ready data products or metrics that agents can query
- A governance instinct: understanding why changes to revenue or customer data need a control owner and a ticket
