<p>BeOne continues to grow at a rapid pace with challenging and exciting opportunities for experienced professionals. When considering candidates, we look for scientific and business professionals who are highly motivated, collaborative, and most importantly, share our passionate interest in fighting cancer.</p><p>We are seeking a <b>Senior Principal Data Engineer</b> to serve as one of the highest-level technical leaders within the Data Engineering organization. Responsible for defining technical strategy, architecting enterprise-scale data platforms, and delivering scalable, secure, and high-quality data solutions.</p><p>This role combines deep expertise in cloud data platforms, software engineering, enterprise data architecture, data modeling, AI-assisted development, and technical governance. The successful candidate will influence technical direction across multiple business domains, establish engineering standards, and mentor engineers while remaining hands-on with architecture and solution design.</p><h3>Key Responsibilities:</h3><h3>Enterprise Data Architecture</h3><ul> <li>Design and evolve enterprise-scale data platform architecture supporting analytical, operational, and AI workloads.</li> <li>Define reusable engineering frameworks, reference architectures, and technical standards.</li> <li>Drive long-term platform strategy focused on scalability, security, performance, and maintainability.</li> </ul><h3>Technical Leadership</h3><ul> <li>Lead architecture reviews, technical design, and engineering governance for strategic initiatives.</li> <li>Partner with engineering leadership to define technology roadmaps and drive engineering best practices.</li> <li>Influence technical decisions across multiple teams without direct people management.</li> </ul><h3>Data Engineering &amp; Data Modeling</h3><ul> <li>Design scalable ETL/ELT frameworks, enterprise data pipelines, and logical and physical data models.</li> <li>Develop reusable, metadata-driven data integration frameworks.</li> <li>Establish standards for data modeling, metadata management, lineage, and performance optimization.</li> </ul><h3>AI-Driven Engineering</h3><ul> <li>Champion AI-assisted software development across the engineering organization.</li> <li>Evaluate and implement AI coding assistants and engineering productivity tools.</li> <li>Build intelligent engineering accelerators, including:<ul> <li>AI-assisted code generation</li> <li>Automated documentation</li> <li>Code review assistance</li> <li>Test generation</li> <li>Data quality validation</li> <li>AI-powered engineering copilots</li> </ul> </li> <li>Drive engineering productivity and innovation through Generative AI.</li> </ul><h3>Cloud &amp; Platform Engineering</h3><p>Provide technical leadership across modern cloud technologies including:</p><ul> <li>Databricks</li> <li>Azure</li> <li>AWS</li> <li>Docker</li> <li>Kubernetes</li> <li>Python</li> <li>SQL</li> <li>Git</li> <li>REST APIs</li> <li>CI/CD</li> </ul><h3>