Job Description At Accelerant, we're not just keeping pace with technological advancements, we're leading the charge. As we refine and expand our operations, we're looking for a forward-thinking Data Engineer to join our dynamic team. As a Data Engineer, you will take on a central role in constructing and optimizing our robust data platform. This platform is at the heart of our operations—it drives our SaaS platform, underpins our internal analytics, and fuels our operational systems. In this role, you'll have the unique opportunity to design and build solutions that don't just deliver insights but lay the foundation for Accelerant's success in the digital landscape. Whether it's shaping unique selling propositions or pushing the boundaries of what our technology can do, your work will influence every corner of our organization. Key Responsibilities - Analyse and ingest new datasets from varied sources - Design, build, and support cloud infrastructure - Design, build, and support AI and ML processes and infrastructure - Design and build modern, metadata driven data pipelines and data streams - Design and build data service APIs - Transform and cleanse complex datasets - Analyse current business practices, processes and procedures - Implement effective metrics and monitoring processes - A commitment to learning and sharing knowledge Required Skills/Experience - 2 or more years’ experience working as a Data Engineer - Experience of developing in AWS - Snowflake - SQL - Python - Experience with DataOps methodologies, tools, and processes. Desirable Skills - dbt - Experience handling structured and unstructured datasets - Experience in AI and Machine Learning - Experienced in real-time and batch mode data ingestion - Experience in Data Warehouse development - General P&C Insurance business knowledge #LI-DNI

• Define and execute the product vision and roadmap for Liftoff’s data infrastructure • Translate complex machine learning and analytics requirements into detailed technical documentation and product specifications • Partner with cross-functional teams across the U.S. and Beijing to design, prioritize, and deliver high-impact data pipelines, APIs, and storage architectures • Establish and monitor data quality, latency, and reliability KPIs • Collaborate with ML and analytics stakeholders to ensure the data platform enables rapid experimentation and model development • Anticipate data and infrastructure needs, proactively shaping architecture and tooling strategy • Advocate for data best practices, including governance, lineage, and documentation across global teams

• Design, build, and optimize scalable backend services supporting both traditional search and AI-powered search systems. • Own the architecture of search-related systems to ensure high reliability, performance, and scalability. • Develop reusable backend frameworks and infrastructure to accelerate search and AI product development. • Collaborate closely with data scientists and AI engineers to enable LLM-powered search, ranking, and agent capabilities. • Continuously improve search performance, including indexing, retrieval, ranking, and latency optimization. • Translate business needs into scalable search solutions. • Drive execution and deliver results in complex or evolving environments.

• Oversee the operational health of the platform. • Maintain and enhance monitoring, logging, and alerting solutions to proactively identify and resolve issues. • Lead incident response and perform root cause analysis for platform-wide problems. • Maintain and enhance the core components of our Azure Databricks environment. • Define the strategic roadmap for the platform, including the adoption of new features and best practices. • Manage the enforcement and enhancement of data security and governance policies. • Implement strategies for cost management and performance tuning at a platform level. • Maintain and enhance automated solutions for provisioning and managing Databricks workspaces. • Serve as a subject matter expert and mentor to other data engineers. • Partner with data engineering and business teams to understand their needs. • Oversee and direct the efforts of 2 platform engineers.