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The Operations & Analytics team powers Veriff’s business engine. We’re tackling the identity crisis at scale and deploying operational excellence to keep Veriff on the cutting edge. It’s a fast-paced market with evolving challenges — and we’re looking for fresh talent to help fill the gaps. Our team blends operational insight and technical depth, combining systems, processes, and analytics to ensure Veriff runs efficiently and intelligently. About the Role As an Analytics Engineer , you'll be responsible for designing clean, reusable data models that unlock operational insights and power data-driven tools — from internal and external self-service interfaces to models that support analytics across Product, Finance, Sales, Marketing and Operations. You’ll work cross-functionally across Data Insights, Product & Engineering, and Business to build analytics systems that scale — focused on real-world use cases. You’ll help us protect honest people online by: Build and maintain sustainable dbt models aligned with business logic and stakeholder workflows Own model development for core operational and customer-facing analytics use cases Support the self-service tooling initiative by building reliable, permissioned data foundations Translate complex raw datasets into clear, documented, analyst-ready structures Define and enforce modeling and documentation standards across the Data Insights team Collaborate with Data Analysts, Data Scientists, Product Managers, and Data Engineers to deliver full-stack data solutions Contribute to long-term improvements in data governance, observability, and testing Reduce single points of failure by distributing model ownership and formalizing critical assets You are the right future Veriffian for the job if: Have 3+ years of experience in analytics engineering or BI development with strong SQL and solid intermediate level Python proficiency Have production experience with dbt in a version-controlled environment Understand scalable data pipeli