Senior Data Engineer

RemoFirst empowers employers to be free from geographical boundaries when accessing talent, allowing employees to pursue opportunities wherever they may exist. We are on a mission to be the FIRST to revolutionise the industry and be a truly generational company. Our platform offers a full range of people management tools, employee benefits like health insurance, and financial benefits, enabling clients to hire anyone from anywhere with one click. RemoFirst manages employees and contractors for Fortune 500 companies (e.g., Microsoft, Mastercard) and the best startups worldwide (e.g., TransferGo).  We are one of the fastest-growing private companies in the USA, recently at 85th position on the Inc. 5000 list of fastest-growing companies in 2025. Backed by $40+M in venture funding, we are scaling rapidly and investing heavily in AI-driven solutions to supercharge our operations. We are looking for a Senior Data Engineer to design, build, and operate a scalable, cloud-native data platform that supports both analytics and AI-driven use cases. This role goes beyond traditional data warehousing .You will work closely with AI engineers to build the data foundation that powers LLM applications, agent-based systems and RAG solutions. You will be responsible for building reliable data pipelines, developing curated data models and products, and ensuring high-quality, trusted data is readily available for analytics and AI workloads.

Key Responsibilities• Design, build and maintain scalable data pipelines using modern data engineering tools (e.g., dbt, Airflow, Prefect). • Develop and maintain dimensional and semantic data models to support analytics and operational use cases. • Build curated data products that support analytics and modern AI workloads. • Design data schemas and storage strategies optimized for both analytical and AI workloads. • Build and maintain version control workflows and isolated development/test environments. • Manage and optimize cloud-based data infrastructure ensuring performance, scalability, reliability and cost efficiency. • Contribute to the architecture and evolution of the organization's modern data platform. • Collaborate closely with AI, Analytics, and Product teams to deliver scalable, high-quality data solutions.