Senior Data Analyst
Natera · San Carlos, CA
About this role
**Senior Data Analyst** **Location**: Hybrid (1 day/week) — San Carlos, CA **Position Summary** Natera is a global leader in cell-free DNA testing, supporting oncology, women’s health, and organ health. In R&D operations data science, you’ll support R&D activities through data analytics and the development of intelligent tools that optimize workflows and processes. As a **Senior Data Analyst**, you will design, prototype, and build a modern, next-generation AI analytics platform to phase out legacy reporting infrastructure. You’ll use AI developer tools (e.g., Claude Code, Gemini) to accelerate design, scripting, and platform prototyping—while applying engineering rigor to audit, validate, and refine AI-assisted output to ensure production-grade quality, data accuracy, and system reliability. **Primary Responsibilities** - **Platform Design & Rapid Prototyping**: Architect, iterate, and build a new R&D analytics platform; prototype scalable analytics solutions and modern self-service data tools. - **AI-Accelerated Development & Rigorous Validation**: Use AI tools (e.g., Claude Code, Gemini, coding assistants) to speed development and automate repetitive tasks; review, debug, unit-test, and validate generated code and analytics logic for correctness, security, and efficiency. - **Data Pipeline & SQL Engineering**: Extract, clean, transform, and model complex multi-source R&D data; develop and optimize high-performance custom SQL; partner with Data Engineers to improve scalability and performance. - **Analytics & Insight Generation**: Translate operational requirements into actionable insights, automated KPI workflows, and modern analytics interfaces that drive R&D decision-making and continuous improvement. - **Stakeholder Collaboration**: Work closely with cross-functional R&D stakeholders and operational teams to define analytics requirements and deliver robust data tools. - **Data Quality & Governance**: Establish validation frameworks, automated monitoring, and data integrity checks to ensure accuracy and consistency across platform outputs. **Qualifications** - **Experience**: 2+ years in data analysis, analytics engineering, or software/data platform development. - **AI Tooling Proficiency**: Practical experience using modern AI developer assistants (e.g., Claude Code, Gemini, GitHub Copilot). - **Analytical Rigor & Data Validation**: Strong ability to independently evaluate, verify, and fine-tune data workflows, queries, and automated outputs. - **Python Proficiency**: Advanced Python for data analysis, pipeline development, and prototyping. - **Advanced SQL Expertise**: Strong skills writing, optimizing, and maintaining complex custom SQL. - **Engineering Best Practices**: Clean, modular, reproducible, well-documented code using version control (Git). - **Agile Problem Solving**: Ability to troubleshoot complex technical and data challenges in a fast-paced environment. - **Communication**: Strong written and verbal communication across technical and non-technical teams. **Nice to Haves** - Experience with cloud data warehouses (e.g., Snowflake) and analytics engineering tools (e.g., dbt). - Experience building custom web-based data applications or internal tools (e.g., Streamlit, Dash, Gradio, or other web frameworks). - Domain knowledge in molecular biology, biochemistry, bioinformatics, operations research, or related biotech fields. - Proficiency in Linux/Unix. **Compensation & Total Rewards** - **Compensation Range**:
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