About the job
About Us
Yodeck is an innovative and rapidly expanding Software-as-a-Service (SaaS) firm dedicated to transforming the $23 billion digital signage market. Our user-friendly, cost-effective, and feature-rich platform is designed to make digital signage accessible, empowering businesses across the globe. Since our launch in 2016, Yodeck has successfully powered over 160,000 screens in diverse settings, from restaurants and retail shops to educational institutions, stadiums, and conference centers. Recognized among the top five digital signage SaaS providers worldwide, we invite inquisitive and talented individuals to join our mission of accelerated growth!
About the Role
We are on the lookout for a skilled Analytics Engineer to serve as a crucial link between data engineering and business analytics. This role will involve designing and constructing robust data models that facilitate insightful reporting and informed decision-making while ensuring data integrity and reliability throughout our organization. You will collaborate closely with analysts, stakeholders, and data engineers to convert business requirements into clean, reusable data structures that enhance BI dashboards and self-service analytics. This is an exciting opportunity for someone passionate about building strong data foundations and advancing data maturity in a dynamic SaaS environment.
Responsibilities
- Design and develop essential data models (Customer, Subscription, Revenue) in Snowflake using dbt, structuring Silver and Gold layers to ensure dependable reporting and analysis across the organization.
- Collaborate with the Head of Data and stakeholders to implement and maintain standardized metric logic (MRR, churn, CAC, retention), ensuring consistent and reusable definitions across all tools.
- Establish data quality checks, testing, monitoring, and documentation in dbt, ensuring transparency and trust in all data outputs.
- Work with analysts and stakeholders to translate business inquiries into structured data models; support BI tools with curated data sources.
- Implement and uphold data contracts and model standards in collaboration with the Data Engineer, minimizing pipeline disruptions and ensuring schema stability.
- Continuously enhance and evolve data models as business needs shift; support the adoption of self-service analytics.
