Senior Analytics Engineer

Material Bank·London, England, United Kingdomsenior

En corto

→Ingeniero de análisis sênior que construye y mantiene modelos de datos confiables en Snowflake y dbt para informes y productos de datos.
→Trabaja en end-to-end: define métricas, crea modelos, dashboards en Tableau/Sigma y asegura precisión en la fuente de verdad del negocio.
→Destaca por ser dueño total del ciclo de vida del análisis, desde conversación con stakeholders hasta mantenimiento y resolución de incidencias.

No se requiere inglés explícitamente, pero el puesto es en UK y el entorno es global.

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¿Qué piden?

✓5+ años en ingeniería de análisis o rol técnico similar con propiedad sobre modelos y reporting.
✓Experto en SQL con datasets grandes y complejos.
✓Experiencia sólida en Snowflake y dbt (modelado dimensional, modelos incrementales, pruebas y documentación).
✓Habilidades avanzadas en Tableau, con experiencia en creación de dashboards de alto valor.
✓Capacidad para garantizar una única fuente de verdad y resolver inconsistencias lógicas en métricas.
✓Capacidad de trabajar en un equipo pequeño, ágil y exigente con alto nivel de autonomía.

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

SnowflakedbtTableauSigmaLookerSnowflake CortexSQLPythonGitCI/CD

¿A quién escribirle en Material Bank?

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Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials. Senior Analytics Engineer, Analytics & Insights London, UK (Hybrid, 2 days in office) Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials. About the role We are looking for a Senior Analytics Engineer to join Analytics & Insights, the team that owns Material Bank's analytics data layer, internal reporting, and data products that support our teams and brand partners. This is a hands-on technical role for someone who wants to own how analytics get built. You will take approved metric definitions and business questions and turn them into the models and metric logic in Snowflake and dbt, the dashboards, and the semantic layer and data products people use every day. You will own the analytics engineering for key areas of the business: understanding what needs to be measured, building the models, validating the logic, delivering the reporting, and keeping it accurate and reliable over time. You will work across multiple departments and across our data products, including embedded analytics for brands. The work varies day to day, and as a team we contribute to everything. What we require Ownership, end to end. You own what you build, from the first stakeholder conversation to the model, the dashboard, and the fix when something breaks. Precision and attention to detail. You understand the nuance behind a number, verify before you publish, and produce work that leaders and brand partners can trust without checking. Appetite for hard work. We are a small, ambitious team with a lot of goals. The work is demanding and the hours vary with what needs to get done. We are upfront about that because it is what the role is. What you'll do Own the analytics engineering for assigned business domains, translating metric definition through data model, dashboard, and insight. Design, build, and maintain documented, production-quality dbt models in Snowflake that turn approved metric definitions into reliable, reusable models and semantic definitions, and power reporting, self-serve, automation, and AI. Identify and resolve technical inconsistencies in metric logic so the business runs on one certified source of truth. Build a small set of high-value dashboards in Tableau (and Sigma, as we evolve the stack). Contribute to the semantic layer so certified metrics are reusable across BI tools, Snowflake Cortex, and embedded analytics. Automate recurring analytics work, with the tests and monitoring that keep it trustworthy. Partner with analysts and stakeholders to interpret data, build context, and surface risks before they are asked. Contribute to brand-facing data products used by account teams and manufacturer partners. What you'll bring 5+ years in analytics engineering, data analytics, or a similar technical analytics role, owning data models and reporting that a business relies on. Expert SQL on large and complex datasets. You write clean, efficient queries and can debug someone else's logic as easily as your own. Strong hands-on Snowflake and dbt (or a comparable modern data stack), including dimensional modeling, incremental models, testing, and documentation. Strong Tableau skills. Sigma, Looker, or similar a plus.

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