Data Analyst – Revenue & Metrics

LaunchDarkly is looking for a Data Analyst to join our Data & Analytics team in India. In this role, you will focus on building and scaling reliable data models, automating reporting, and supporting global analytics delivery.

You will partner closely with the Senior Data Analyst (Revenue & Metrics), Data Engineering, and business stakeholders to translate business logic into clean, scalable datasets. This role plays a key part in ensuring that defined metrics (e.g., ARR, NRR) are consistently implemented, automated, and delivered across the organization.

Responsibilities:

Data Modeling & Transformation Build and maintain scalable data models using modern tools (e.g., Snowflake, dbt). Translate defined business logic (e.g., ARR calculations) into clean and reusable datasets.

Metrics Implementation Implement and maintain standardized metrics (e.g., ARR, NRR, churn) in the data layer. Ensure consistency across dashboards and reports.

Automation & Pipeline Support Work with Data Engineering to automate data pipelines and reduce manual reporting processes.

Dashboarding & Reporting Develop and maintain dashboards that provide consistent and reliable visibility into business performance.

Data Quality & Validation Validate data outputs, identify inconsistencies, and support reconciliation efforts across systems (e.g., Salesforce, billing systems).

Global Collaboration Partner with teams across the US and EMEA to deliver timely and high-quality analytics outputs.

Qualifications:

Typically requires a minimum of 5 years of related experience in data analytics, business intelligence, or analytics engineering

Strong SQL skills and experience working with structured and large datasets

Experience with modern data tools (e.g., Snowflake, dbt, Looker or similar)

Experience building and maintaining data models and dashboards

Experience implementing business logic into data transformations

Strong attention to detail and ability to ensure data accuracy

Ability to work with global teams across time zones