Analytics Engineer

Required Experience & Education Bachelor's degree in computer science, Information Systems, Engineering, Data Science, Life Sciences, Business, or a related field, or equivalent practical experience. Minimum 8 years of progressive experience in technical program management, technical product or project delivery, business analysis, or data and analytics delivery. Experience in an oncology-focused biotechnology or biopharmaceutical environment, preferably supporting commercial readiness, launch planning, forecasting, or related business operations. Proven success translating complex needs into delivery-ready requirements, user stories, acceptance criteria, process or data flows, and mock views. Experience partnering with data engineering teams on pipelines, integrations, transformations, data models, data quality, and analytics or reporting use cases. Strong Agile delivery skills and hands-on use of Azure DevOps, Smartsheet, or comparable platforms to manage plans, backlogs, risks, and reporting. Ability to work on-site during the initial onboarding, discovery, and team-integration period. Preferred Qualifications Experience with forecasting, launch-readiness metrics, master data, or executive reporting in a regulated environment; relevant PMP or Agile certification is a plus. Key Competencies / Soft Skills Builds trust quickly with commercial, finance, and executive stakeholders in a fast-moving cross-functional, matrixed biotech environment. Translates ambiguous business needs into clear, structured requirements. Communicates technical tradeoffs in plain business language for non-technical stakeholders. Tools & Technologies Azure DevOps and Smartsheet SQL (query and validate data, support UAT) and BI tools (Power BI preferred) Snowflake or comparable cloud data platform (preferred) #J-18808-Ljbffr Openkyber