Senior Analytics Engineer

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.

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.

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 anddbt, 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 itaccurateand 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.

• 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 forhard 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.

• Own the analytics engineering for assigned business domains, translating metric definition through data model, dashboard, and insight.
• Design, build, andmaintaindocumented, production-qualitydbtmodels 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.

• 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 anddbt(or a comparable modern data stack), including dimensional modeling, incremental models, testing, and documentation.
• Strong Tableau skills. Sigma, Looker, or similar a plus.
• Strong judgment on metric design: grain, denominators, filters, time zones, deduplication, and the ways a correct number can still mislead.
• Commercial sense and curiosity. You want to understand why a number matters, can explain what a change means for the business, and hold a position under questioning.
• An automation mindset. When you see something repetitive or fragile, your instinct is to find a better way to build it.
• Comfort working across several domains at once, prioritizing your own work, and managing stakeholders directly.
• Clear, concise…