GTM Strategy Lead Data Analyst

GTM Strategy Lead Data Analyst OpenGov is the leader in AI and ERP solutions for local and state governments in the U.S. More than 2,000 cities, counties, state agencies, school districts, and special districts rely on the OpenGov Public Service Platform to operate efficiently, adapt to change, and strengthen the public trust. Category-leading products include enterprise asset management, procurement and contract management, accounting and budgeting, billing and revenue management, permitting and licensing, and transparency and open data. These solutions come together in the OpenGov ERP, allowing public sector organizations to focus on priorities and deliver maximum ROI with every dollar and decision in sync. Learn about OpenGov’s mission to power more effective and accountable government and the vision of high-performance government for every community at OpenGov.com http://OpenGov.com. JOB SUMMARY We are seeking a highly analytical and business-minded GTM Strategy & Analytics Lead Data Analyst to join our GTM Strategy & Analytics team. This role is critical in transforming complex data into actionable insights that drive strategic decision-making and optimize business performance across various functions. The ideal candidate will possess a strong blend of technical data analysis and analytics engineering skills, a keen understanding of business operations, and the ability to communicate complex findings to non-technical stakeholders effectively. You will partner closely with operations leadership, product managers, marketing teams, and other cross-functional departments to identify opportunities, measure impact, and inform our strategic direction. RESPONSIBILITIES - Cross-functional Partnership: Embed deeply with stakeholders across Product, Marketing, Sales, Finance, Operations to understand their analytical needs, translate business questions into data models, and deliver data-driven recommendations and data assets that support decision making. - Data Subject Matter Expertise: Own the creation of high impact data assets that connect customer and/or internal activity to outcomes and provide a scalable model for future analysis. Partnering with Data Engineering and AI Ops you will architect a robust semantic layer, creating datasets to be leveraged across traditional reporting tools and conversational AI front ends, owning the end-to-end lifecycle of data models within the warehouse and business intelligence tools. - Data Integrity & Governance: Work with data engineering, systems and operations and other teams to ensure data quality, consistency, and accessibility for analytical purposes, contributing to a robust data infrastructure. - Deep Dive Analysis: Conduct comprehensive ad-hoc analyses to investigate specific business problems, evaluate the effectiveness of strategic initiatives, and answer critical "why" questions. - Performance Measurement & Reporting: Partner with operations and field stakeholders to automate existing reporting assets, creating data models & structures to support easy and repeatable analysis. - Data Storytelling & Communication: Present complex analytical findings and recommendations in a clear, concise, and compelling manner to both technical and non-technical audiences. - Forecasting & Modeling: Build operational forecasts, predictive models, and scenario planning tools to anticipate future trends and inform resource allocation and risk to the business. - Tool & Technology: Utilize BI tools (e.g., Looker, Tableau, Power BI), SQL, data base tools (DBT, Snowflake, etc.) and programming languages (e.g., Python, R) to extract, transform, and analyze data efficiently. REQUIREMENTS - Bachelor's degree in a quantitative field such as Engineering, Economics, Statistics, Mathematics, Computer Science, or a related discipline. - 6-8 years of experience in data analytics, analytics engineering, business intelligence, or a similar quantitative role, with a strong emphasis on deriving strategi ... (truncated, view full listing at source)