Staff Analytics Engineer (1 Year Fixed-Term Contract)

SHAPE THE FUTURE OF PRIVACY WITH USERCENTRICS Hybrid position - 2/3 days in the office 1 year fixed-term contract Usercentrics is a global leader in the field of consent management platforms (CMP). We follow our company vision to build a world where user privacy enables a thriving digital ecosystem. Our mission is to provide privacy solutions that empower organizations to embrace data privacy while building trust with their users through freedom of choice. With our product, businesses can collect, manage and document user consents on websites and apps, and achieve full compliance in accordance with global privacy regulations while facilitating high consent rates and building trust with their customers. We’re looking for an experienced Staff Analytics Engineer to own the design and delivery of scalable data models and data products across our data warehouse, semantic layer, and reporting layer. Reporting to the Director of Analytics, you will enable critical decision making across the business, from marketing and product to commercial operations. This is a senior individual contributor role with technical leadership responsibilities. You will not manage a team initially, but you will set standards and mentor others. This role may evolve into a people management position as the team scales. Your Tasks Drive the development and expansion of our Data Warehouse and BI solutions, with a focus on simplicity, scalability, and reliability, ensuring they grow sustainably. Own and evolve the Analytics Engineering strategy, including architectural decisions, modeling standards, and the long term roadmap. Collaborate with Data Analysts, Data Scientists, and backend engineers to deliver trusted, well modeled, analysis-ready datasets. Apply software engineering best practices across the analytics codebase, including version control, code reviews, automated testing, lineage, and continuous integration. Evaluate, select, and deploy tools and frameworks to strengthen data quality, governance, and reliability. Partner closely with business stakeholders to design and scale the semantic layer to support diverse and evolving business needs, enabling and accelerating self service analytics. Act as a go to person for Data Analysts and Data Scientists, providing guidance to improve pipelines and remove inefficiencies, redundancies, and technical bottlenecks. Mentor and support other team members as the team scales, contributing to capability building, onboarding, and continuous knowledge sharing. Bring strategic thinking and innovative ideas to help shape a growing team and deliver meaningful business impact at scale.