Analytics Engineer
Drive, Don't Wait: Actively seek out business needs, identify opportunities for improvement, and deliver solutions—rather than waiting for assignments. Own the Data Lifecycle: Proactively engage with business stakeholders (Sales, Finance, Customer Success, Product, etc.) to pull requirements and translate complex business questions into technical data models. Single Source of Truth (SSoT): Collaboration with Data Engineer to design, develop, and maintain a unified Customer 360 Single Source of Truth by integrating and transforming data from diverse SaaS applications (CRM, billing, CLM, product usage, etc.). BI Development: Build and deploy high-impact Power BI dashboards and reports that visualize key SaaS metrics (MRR, Churn, CAC, LTV, product adoption) and drive measurable business outcomes. Self-Service Enablement: Develop robust, secure, and well-documented datasets in Power BI to facilitate self-service analytics and data literacy across the organization. Champion Data Stewardship: Promote best practices for data quality, documentation, and governance, ensuring analytical assets are reliable and trusted. Data Modeling: Architect and build high-performance, structured dimensional models within Microsoft Fabric, optimized for analytics. Data Transformation: Develop, test, and deploy production-grade data transformation logic using advanced SQL and Python/PySpark Notebooks. Automation (Bonus): Familiarity with Microsoft Power Apps and Power Automate is a plus, helping streamline and automate manual data and reporting workflows. You function as the end-to-end owner of data solutions, from requirements gathering to dashboard deployment. The Customer 360 SSoT becomes the trusted, go-to source for strategic reporting and decision-making. Staff spend less time searching for and preparing data, and more time solving customer problems. Data is accessible, reliable, and drives the adoption of self-service analytics. Measurable improvements in data quality, accessibility, and dashboard usage.
Analytics Engineer
Drive, Don't Wait: Actively seek out business needs, identify opportunities for improvement, and deliver solutions—rather than waiting for assignments. Own the Data Lifecycle: Proactively engage with business stakeholders (Sales, Finance, Customer Success, Product, etc.) to pull requirements and translate complex business questions into technical data models. Single Source of Truth (SSoT): Collaboration with Data Engineer to design, develop, and maintain a unified Customer 360 Single Source of Truth by integrating and transforming data from diverse SaaS applications (CRM, billing, CLM, product usage, etc.). BI Development: Build and deploy high-impact Power BI dashboards and reports that visualize key SaaS metrics (MRR, Churn, CAC, LTV, product adoption) and drive measurable business outcomes. Self-Service Enablement: Develop robust, secure, and well-documented datasets in Power BI to facilitate self-service analytics and data literacy across the organization. Champion Data Stewardship: Promote best practices for data quality, documentation, and governance, ensuring analytical assets are reliable and trusted. Data Modeling: Architect and build high-performance, structured dimensional models within Microsoft Fabric, optimized for analytics. Data Transformation: Develop, test, and deploy production-grade data transformation logic using advanced SQL and Python/PySpark Notebooks. Automation (Bonus): Familiarity with Microsoft Power Apps and Power Automate is a plus, helping streamline and automate manual data and reporting workflows. You function as the end-to-end owner of data solutions, from requirements gathering to dashboard deployment. The Customer 360 SSoT becomes the trusted, go-to source for strategic reporting and decision-making. Staff spend less time searching for and preparing data, and more time solving customer problems. Data is accessible, reliable, and drives the adoption of self-service analytics. Measurable improvements in data quality, accessibility, and dashboard usage.