Senior Business Analytics Engineer - India

Overview

Senior Business Analytics Engineer to own dbt transformation logic and semantic-layer metric definitions on the internal data warehouse, produce revenue numbers (ARR, CARR and related metrics) for Sales, Finance, Fund Administration and leadership, and link business stakeholders with the Data Engineering team.

What you'll do

• 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 such as 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 the Lead Business Systems Analyst and Integrations Engineers so the commercial model and source data are reportable from the start.
• 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.

What you'll need

• 5+ years in analytics engineering, data engineering or business intelligence.
• 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.

Nice to have

• 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 a change to revenue or customer data needs a control owner and a ticket.

Details

• Location: India.
• Overlap of a few hours with US time zones is required.