Senior Business Analytics Engineer - India

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.

About your role

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.

What you'll do

Transformation & data modeling

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

Semantic layer & metric definitions

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

Requirements translation

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

AI-assisted reporting & measurement

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

Governance & controls

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

What success looks like

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

Required Qualifications

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

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

Benefits

Health, dental, and vision care for you and your family

Life insurance

Mental wellness coverage

Fertility and growing family support

Flex Time Off in addition to company-paid holidays

Paid family leave, medical leave, and bereavement leave policies

Retirement savings plans

Allowance to customize your work and technology setup at home

Annual professional development stipend

Your recruiter can provide additional details about compensation and benefits.