Analytics Engineer

Analytics Engineer

Yodeck is a fast-growing Software-as-a-Service (SaaS) company that is laser-focused on disrupting the $23B digital signage industry. Yodeck's affordable, easy-to-use, and feature-rich solution has been developed to democratize digital signage and empower with it any and every business around the world. Yodeck was first introduced in 2016 and now powers over 160,000 screens across every type of business from restaurants and retail stores, to schools, stadiums and conference halls. Yodeck is now in the top 5 of digital signage SaaS platforms in the world, and we are looking for curious and smart people to drive even faster!

We're looking for an Analytics Engineer to bridge the gap between data engineering and business analytics, enabling reliable, scalable, and well-structured data across the organization. In this role, you will design and build robust data models that power reporting, insights, and decision-making, while ensuring consistency, quality, and trust in our data ecosystem.

You'll work closely with analysts, stakeholders, and data engineers to translate business needs into clean, reusable data structures, supporting everything from BI dashboards to self-serve analytics. This is a great opportunity for someone who enjoys building strong data foundations, shaping metric definitions, and driving data maturity in a fast-growing SaaS environment.

Responsibilities include:

• Design and build core data models (Customer, Subscription, Revenue) in Snowflake using dbt, structuring Silver and Gold layers to support reliable reporting and analysis across the business
• Implement and maintain standardised metric logic (MRR, churn, CAC, retention) in collaboration with the Head of Data and stakeholders, ensuring consistent, reusable definitions across all tools
• Implement data quality checks, testing, monitoring and documentation in dbt, ensuring trust and transparency in all data outputs
• Partner with analysts and stakeholders to translate business questions into structured data models; support BI tools with curated data sources
• Implement and maintain data contracts and model standards in collaboration with the Data Engineer, reducing pipeline breakages and ensuring schema stability
• Continuously improve and evolve data models as business needs change; support self-serve analytics adoption