Senior Business Analytics Engineer - India

Private markets are one of the largest, most complex, and most underserved corners of global finance. Our mission at Juniper Square is to unlock their full potential. We’re the Operations Partner trusted by 2,300+ GPs, unifying technology, data, and fund administration services into a single platform that helps GPs move faster, make better decisions, and scale with precision. With $300B+ under administration and 700,000+ LPs on platform, we’ve built the scale to match our ambition. And with JunieAI, our purpose-built AI platform, we’re reimagining how private markets operate, embedding intelligence across every workflow. Founder-led since 2014, backed by $350M+ in funding, and now 1,000+ employees strong, we’re building a company designed to shape the future of private markets for decades to come.

Our culture is built for people who want to do ambitious, meaningful work alongside exceptionally talented teammates. We think like owners, move with urgency, and take pride in solving hard problems that truly matter to our customers and the future of private markets. We believe the best ideas come from open debate, deep collaboration, and diverse perspectives, which is why we believe transparency is the default and feedback makes us stronger. If you’re energized by high standards, rapid growth, and the opportunity to help define a category at a pivotal moment, come join us!

Juniper Square offers employees a variety of ways to work, ranging from a fully remote experience to working full-time in one of our physical offices. We invest heavily in digital-first operations, allowing our teams to collaborate effectively across 27 U.S. states, 2 Canadian Provinces, India, Luxembourg, and England. We also have physical offices in San Francisco, New York City, Mumbai and Bangalore for employees who prefer to work in an office some or all of the time.

We're hiring a Senior Business Analytics Engineer to produce the revenue numbers Juniper Square runs on. This role produces one computed definition of metrics for different ARR metrics for Sales, Finance, Fund Admin and leadership teams at different levels.

You'll own the dbt transformation logic and the semantic-layer definitions on top of our internal data warehouse, as part of a company-wide rebuild of how revenue moves from quote to recognized revenue. You'll also be the link between business stakeholders and our Data Engineering team, turning business questions into precise technical requirements. And you'll build the AI-assisted reporting layer that lets people and AI agents get the same trustworthy answer from the same source.

• Own dbt models for revenue and customer data sourced from CRM, CPQ, billing, and ERP systems

• Model the chain from quote to order to provisioning to invoice to recognized revenue at the entity and service grain

• Move reporting-level data generation out of Salesforce and into the warehouse, where other systems can consume it

• Define and govern certified metrics like ARR and CARR and the dimensions behind them

• 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 the Finance close so the numbers tie out

• Translate business questions from Sales, Finance, Fund Administration, and leadership into technical requirements for Data Engineering, covering source data, grain, freshness, and quality

• Work with our Lead Business Systems Analyst and Integrations Engineers so the commercial model and source data are reportable from the start

• 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 the ability to work through legacy queries you didn't write

• 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

• 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: you understand why a change to revenue or customer data needs a control owner and a ticket

• 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 stakeholders

• Stand up measurement for the Lead-to-Cash program so monthly progress is shown in numbers rather than status updates

• Apply access controls, data classification, and change management suited to financial and customer data in SOX, SOC 1, and SOC 2 scope

• First 90 days: own the core revenue dbt models, and publish draft definitions for ARR, CARR, and backlog reviewed with Finance

• Within 6 months: a certified semantic layer for revenue metrics, and the first in-service ARR figure computed from systems

• Within 12 months: one number of record for each revenue metric, used across Finance, Sales, and leadership, with AI-assisted reporting live