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Vacantes / Kpler

Senior Data Analyst – Revenue Intelligence

Kpler·Londonsenior

En corto

  • →Analista de datos senior que construye y mantiene modelos de ingresos en BigQuery y Looker.
  • →Se enfoca en métricas clave como ARR, retención, churn y renovaciones, sirviendo a ventas, éxito del cliente y finanzas.
  • →Destaca la responsabilidad total sobre datos de ingresos que impactan decisiones comerciales y financieras.

Proficiency in English is required for day-to-day collaboration with international teams.

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¿Qué piden?

  • ✓5+ años en análisis de datos o BI, con 2+ años gestionando un dominio de datos desde cero.
  • ✓Experiencia sólida en SQL y BigQuery o data warehouse en la nube.
  • ✓Conocimiento avanzado en modelado de datos: gránularidad, deduplicación, dimensiones lentas.
  • ✓Experiencia probada con Looker y LookML, incluyendo modelos, Explores y dashboards.
  • ✓Experiencia con datos de SaaS B2B: Salesforce y/o sistemas de facturación como Stripe.
  • ✓Capacidad de explicar métricas a stakeholders no técnicos y colaborar con múltiples equipos.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

BigQueryLookerLookMLSQLSalesforceStripeAI-assisted toolsVersion controlPeer reviewTesting

¿A quién escribirle en Kpler?

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At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors. Since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms. Our team of over 850 experts from 69 countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. Join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success. 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. Essential: 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.

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