This role is for one of Weekday’s clients
Salary range: Rs 1500000 - Rs 2500000 (ie INR 15 - 25 LPA)

Min Experience: 2+ years
Location: Remote (India), India
JobType: full-time

This role owns the definitions, certification, and quality of the company's core metrics — the numbers the Exec team and Board use to measure the business, such as ARR, ACV, NDR, GDR, and Customer Count. You will be the single source of truth for how these metrics are defined and calculated, working closely with Finance, GTM, and Product/Eng to keep definitions consistent and to close the gaps that currently cause reporting to diverge across teams. This role is central to the boundary the team is drawing between company-wide metrics (owned centrally) and function-specific operational analytics (owned by the functions).

Requirements

Responsibilities

• Metrics Definition & Governance — Define, document, and certify the company's core metrics (ARR, ACV, NDR, GDR, Customer Count, Employee Count) so there is one governed version of each.

• Company level Reporting — Own the certification process for metrics used in Company-level reporting, ensuring accuracy and consistency release over release.

• Data Quality & Reconciliation — Identify and resolve inconsistencies across source systems (Salesforce, NetSuite, CS tools, product data) that feed governed metrics.

• Governance Standards — Establish data quality controls, lineage, and ownership standards that scale as the team expands.

• Automation Roadmap — Partner with BI / Data Products & AI and Data Engineering to move metrics from manual reconciliation toward automated, self-service reporting.

• Cross-Functional Alignment — Act as a named point of contact for GTM, G&A, and Product/Eng stakeholders on metric questions and definitional changes, without taking on their function-specific operational analytics.

Must Have

• Experience owning or defining company-wide business metrics (e.g., ARR, NRR/NDR, GDR, customer counts) in a B2B SaaS environment.

• Strong SQL skills and experience working with complex, multi-system datasets.