Senior Data Analyst – Revenue Intelligence at Kpler in London

Job description

• As a Senior Data Analyst in Kpler’s Business Intelligence team, you will own the revenue intelligence pillar, building and maintaining the data models and reporting that help the business understand how we generate revenue - including ARR, retention, pipeline, churn, and renewals.
• You will work with data from Salesforce and subscription billing systems, model it in BigQuery, and serve it through Looker and AI-assisted tools.
• This role sits between data engineering and commercial analytics. One week you might be fixing a revenue pipeline or investigating a data quality issue; the next, you’ll be explaining a retention trend to Finance or helping Sales and RevOps understand their data. You’ll have the opportunity to own the numbers that commercial and finance teams rely on to make decisions.

Responsibilities

• Own and maintain governed revenue datasets in BigQuery, powering ARR, GRR, NRR, pipeline, churn, and renewal reporting across Sales, Customer Success, RevOps, and Finance.
• Model data from Salesforce and subscription billing systems into clean, documented reporting tables, with clear data grain, deduplication rules, and metric definitions.
• Build and maintain LookML models, Explores, and dashboards used for revenue reporting, ensuring consistent naming, definitions, documentation, and data quality standards.
• Own analytics delivery end to end, from understanding stakeholder requirements and modelling data through to dashboard development, testing, and documentation.
• Contribute to Kpler’s internal AI revenue analytics tools by curating governed datasets, maintaining reference documentation, and testing outputs against trusted source data.
• Build monitoring and data quality checks to identify issues such as duplicates, mixed-grain fan-out, missing filters, and reconciliation gaps before they impact stakeholders.
• Investigate and resolve revenue data escalations, addressing root causes and improving the underlying data processes to prevent recurring issues.
• Apply software engineering practices to the BI codebase, including version control, peer review, testing, and documentation.
• Work directly with Sales, Customer Success, RevOps, SalesOps, IT, Product, and Finance to turn business questions into clearly defined metrics and analytical deliverables.
• Explain revenue metrics and analytical outputs clearly to non-technical stakeholders, helping teams understand and self-serve their data.
• Use AI tools to accelerate query writing, documentation, analysis, and quality checks, and share effective approaches with the wider team.

Requirements

• 5+ years of experience in analytics, Business Intelligence, data analysis, or a related data role, with at least 2 years owning a data domain end to end.
• Strong experience with SQL and hands-on experience with BigQuery or an equivalent cloud data warehouse.
• Strong understanding of data modelling concepts, including data grain, dimensional modelling, deduplication, and slowly changing dimensions.
• Production experience with Looker and LookML, including building and maintaining data models, Explores, and dashboards.
• Experience working with B2B SaaS data, ideally including CRM data such as Salesforce and/or subscription billing data such as Stripe or similar platforms.
• Experience working with revenue metrics such as ARR, NRR, GRR, churn, pipeline, and renewals.
• Comfortable working with Git workflows and treating BI code and data models as production software.
• Strong communication skills, with the ability to explain technical concepts and data clearly to non-technical stakeholders.
• Professional-level English, written and spoken.
• Experience with Python for data wrangling or automation.
• Experience with dbt or similar data transformation tools.
• Experience working with AI-assisted analytics or AI tools in a data environment.
• Experience working in an async and remote environment across multiple time zones.

Skills

Required

• SQL
• Looker and LookML
• Git workflows
• Communication skills
• Professional-level English

Preferred

• Python
• dbt or similar data transformation tools
• AI-assisted analytics or AI tools
• Async and remote work across time zones