Veracyte, Inc.

Manager

• Serve as the analytics lead supporting Commercial, Finance, Operations, and related organizational functions
• Act as a thought partner to operational and commercial leadership, prioritizing analytical investments, defining success metrics, and measuring business outcomes
• Collaborate cross-functionally to align analytical solutions with strategic priorities and measurable business value
• Design, develop, and maintain scalable analytical solutions using SQL, Python, Snowflake, Tableau, Power BI, and modern cloud-based data platforms
• Perform statistical analysis, forecasting, segmentation, hypothesis testing, predictive modeling, and exploratory data analysis
• Partner with Data Engineering, IT, and Master Data Management teams to define data requirements, improve data quality, optimize data pipelines, and enhance enterprise data architecture
• Build and maintain semantic data models, reusable datasets, KPI frameworks, and standardized metrics
• Support enterprise data governance by validating source system integrity, documenting metric definitions, monitoring data quality, and promoting reporting consistency
• Leverage AI, machine learning, and advanced analytics to improve forecasting accuracy, automate decision support, and uncover business insights

Manager, Business Analytics

Data Engineer

• Manage and develop a team of data engineers, including talent planning, hiring, coaching, performance management, career development, and team effectiveness
• Guide architecture, design reviews, code quality, troubleshooting, and key implementation decisions
• Translate business and scientific requirements into platform capabilities, delivery plans, and measurable outcomes
• Establish and maintain data platform standards, governance practices, architectural guidelines, and operational processes
• Make architectural decisions using AWS services and related technologies such as Snowflake
• Improve CI/CD, automated testing, observability, lineage, documentation, security, privacy, and code quality
• Partner with Analytics, Data Science, Product, Clinical, Laboratory, Software Engineering, Security, and IT teams
• Ensure data-platform security, regulatory compliance, privacy, and quality-management requirements
• Drive platform delivery and operational excellence, including production reliability
• Balance delivery priorities, operational support, platform enhancements, technical debt, vendors, and resources
• Evaluate emerging technologies and recommend adoption
• Communicate technical decisions, risks, recommendations, and trade-offs to stakeholders and leaders
• Model collaborative and inclusive leadership

Manager, Business Analytics

Senior Manager, Data Engineering