Data Solution Engineer

Imagine if you had the skills, knowledge, and teammates to both understand the root of the world’s most pressing problems and build the technologies and companies best positioned to solve them. RA Capital has done exactly that for more than two decades, backing bold ideas in medicines to further human health and now expanding into Planetary Health to improve how efficiently we utilize the world’s precious resources. RA Capital is among the leading providers of capital and services to the most promising innovators in the world. We invest flexibly—seed to IPO and beyond, anywhere in the world—with $10 B+ under management and a culture that prizes curiosity, rigor, and collaborative debate. We are investors who not only fund companies but get elbow deep in building them. From helping them recruit talent to helping them recruit patients for their studies to helping match them to strategic partners and even going to Washington to win reforms, RA Capital’s large team has people with nearly every relevant expertise one might need to turn an idea into a cure that actually helps people. If you live for first-principles problem-solving with great colleagues, thrive on complexity, and want to do meaningful work that ripples across industries and ecosystems, you’ll feel at home at RA Capital. Here, questions are welcomed, ideas are tested, and victories are shared. Even our lawyers are c [... source excerpt omitted ...] iosity, experimentation, and ownership are highly valued — and where the systems you build directly contribute to funding innovations that can improve and extend human lives. Key Responsibilities Design and deliver end-to-end data and analytics solutions, from initial concept and MVP through production deployment Build dashboards and analytical applications that provide actionable insights to investment and business stakeholders Develop and manage scalable data pipelines in partnership with the Data Engineering team, while independently owning lighter-weight workflows and integrations Support and administer modern cloud data platforms including Databricks, Snowflake, Sigma Comput [... source excerpt omitted ...] and knowledge sharing across the organization Contribute to a collaborative, mentorship-driven engineering culture focused on continuous improvement and technical excellence Key Requirements Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Analytics, or a related technical field 2–5 years of experience building data, analytics, or business intelligence solutions in a professional environment Experience working with modern cloud-based data platforms and analytics tooling Healthcare, biotechnology, life sciences, and/or financial services experience strongly preferred Experience working in fast-paced, highly collaborative environments wit