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Senior Analytics Engineer

London, UK

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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 work across multiple departments and across our data products, including embedded analytics for brands.

  • Own the analytics engineering for assigned business domains, translating metric definition through data model, dashboard, and insight.

  • Build a small set of high-value dashboards in Tableau (and Sigma, as we evolve the stack).

From the employer’s posting
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.
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
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.

Tools in this posting

  • SQL
  • ClickHouse
  • Sigma
  • Snowflake
  • Tableau
  • Python
  • dbt
Source — Tool mentions in context
- 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.
- Semantic layers and AI-assisted analytics (Snowflake Cortex, dbt Semantic Layer, or similar) - Embedded or customer-facing analytics (ClickHouse, Preset, or similar) - Experimentation and causal methods: A/B testing, cohort analysis, difference-in-differences
- 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.
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.
- 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.
- 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.
- Event and behavioral data (Segment, GA4, or similar) - Semantic layers and AI-assisted analytics (Snowflake Cortex, dbt Semantic Layer, or similar) - Embedded or customer-facing analytics (ClickHouse, Preset, or similar)
- 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. - Strong judgment on metric design: grain, denominators, filters, time zones, deduplication, and the ways a correct number can still mislead.
Helpful, not required: - Python for automation and data validation - Marketplace, e-commerce, or B2B SaaS analytics
What success looks like In your first 30 days you understand the stack, the models, the people, and the priorities in your domains, and you have your first dbt change merged. By 60 days you are producing real work independently: agreed metric definitions implemented, your first certified models and dashboards in use, and a plan for the first manual workflow you will automate.

Job description

View original posting ↗

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. 
  • 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 communication and the ability to explain technical concepts to non-technical audiences. 

Preferred 

Helpful, not required: 

  • Python for automation and data validation 
  • Marketplace, e-commerce, or B2B SaaS analytics 
  • Event and behavioral data (Segment, GA4, or similar) 
  • Semantic layers and AI-assisted analytics (Snowflake Cortex, dbt Semantic Layer, or similar) 
  • Embedded or customer-facing analytics (ClickHouse, Preset, or similar) 
  • Experimentation and causal methods: A/B testing, cohort analysis, difference-in-differences 
  • Catalog, product attribute, or search data 

What success looks like 

In your first 30 days you understand the stack, the models, the people, and the priorities in your domains, and you have your first dbt change merged. 

By 60 days you are producing real work independently: agreed metric definitions implemented, your first certified models and dashboards in use, and a plan for the first manual workflow you will automate. 

By 90 days stakeholders treat you as their analytics partner rather than a request queue. Your models are trusted, your dashboards are used without hand-holding, and your automation is reducing real manual effort. 

This is a senior individual-contributor role with broad ownership and hands-on responsibility. Direct people management is not required. 

What you'll get:

  • Our people: If you thrive in an inclusive, innovative, and fast-paced organization, look no further! You will get to work alongside some of the brightest minds - Join a genuinely fun and supportive workplace where we keep our employees consistently engaged through internal communication and corporate events
    Relaxation and Celebrations: Generous PTO, Paid National Holidays, and even more (ask us about this when we connect).
    Health Benefits: We contribute to your medical healthcare
    rowth: We’ll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters!
    Flexible Work Schedules: With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both.
  • Application Process: Interested candidates should submit a resume and cover letter outlining their qualifications and relevant experience. We are committed to diversity and encourage individuals from all backgrounds to apply. 

Material Bank connects design professionals to hundreds of manufacturers through facilitating brand discovery, sales rep engagement, and material sampling. Our powerful material database and proprietary robotic distribution facility allow members to order samples to be delivered free of charge overnight.Material Bank was founded by Adam Sandow in 2018 and has deeply transformed how the Architecture and Design industry works in the United States. It’s an exciting time for the company - Material Bank is growing rapidly and expanding the business to Europe with regional headquarters based in Paris, and offices in London and Stuttgart. Candidates who join us will have the unique opportunity to define, build, and shape our European business.

Material Bank uses your information to process your current application and offer you job opportunities in the future. You have the right to access, rectify, and erase this information, as well as to limit its use or object to it and give directives on its fate after your death. For more information, please consult our privacy policy: https://www.materialbank.eu/privacy-policy

 

What you’ll get from us:

  • Our people: We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution.
  • Relaxation and Celebrations: Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect). 
  • Health Benefits: We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program. 
  • Plan for your Retirement: 401(k) eligible after your first 90 day's employed!
  • Giving Back: We sponsor multiple events throughout the year to help out our communities. 
  • Growth: We’ll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters! 
  • Flexible Work Schedules: With business units and employees across the globe, Material Technologies has embraced a hybrid  working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both.  

Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.

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Location & working pattern

London, UK

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.
More source context
- Growth: We’ll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters! - Flexible Work Schedules: With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both. Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.

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Status in our records
Active
First seen by us
Sep 29, 2026
Recorded sightings
3
Last seen by us
Oct 7, 2026
Employer says posted
Sep 25, 2026

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