Analytics Engineer-Operations

About the company

Pano AI provides a managed wildfire detection platform combining panoramic cameras, AI smoke/fire models, human analysts, satellite, weather and GIS data, triangulation, GPS alerts to first responders and utilities.

About this role

HELP US TACKLE THE GROWING WILDFIRE CRISIS WITH THE LATEST ADVANCEMENTS IN AI AND IOT WHO WE ARE The challenge: Every minute matters in wildfire response. As climate change increases the frequency and intensity of wildfires—with longer fire seasons, drier fuels, and more extreme weather—new ignitions can spread rapidly, putting communities, critical infrastructure, and ecosystems at risk. Today, many wildfires are first reported by members of the public, meaning it can take valuable time to detect a fire, confirm its location and size, and mobilize responders. Fire agencies need faster, more reliable ways to detect, verify, and pinpoint new ignitions so they can respond quickly and prevent small fires from becoming catastrophic events. About Pano AI: Pano AI is the leader in AI-powered wildfire detection and intelligence, helping fire professionals detect, respond to, and contain wildfires faster and more safely. Our platform combines advanced hardware, software, artificial intelligence, satellite imagery, and other data sources to provide real-time situational awareness and actionable intelligence. Using a network of ultra-high-definition, 360-degree cameras positioned across high vantage points, Pano AI delivers a real-time view of wildfire activity, enabling faster, more informed decision-making when every second counts. We are a team of more than 175 people working in a hybrid-remote environment across North America and Australia, with headquarters in San Francisco. Our customers include government agencies, utilities, insurers, and private landowners who rely on Pano AI to help protect people, property, and natural landscapes. Pano AI currently serves customers across the United States, Australia, and Canada, monitoring more than 50 million acres worldwide. Our values are part of everything we do at Pano AI. They guide how we work together, how we serve our customers, and how we approach our mission. Impact: As we scale our business, we grow our impact—enabling emergency managers to protect people, infrastructure, and the environment from devastating wildfires. Service: We serve those who serve, and the teammates beside us. Trust: We earn trust through integrity, accountability, and an obsession with quality so that our partners can rely on us. Excellence and Speed: We produce exceptional work quickly because our mission demands both precision and urgency. Innovation: We apply cutting-edge technology to what we build and how we work. Our work has been recognized by Fast Company as one of the Top 10 Most Innovative AI Companies in 2023 https://www.fastcompany.com/90846670/most-innovative-companies-artificial-intelligence-2023 and one of the World's Most Innovative Companies in 2026 https://www.fastcompany.com/91502951/pano-ai-most-innovative-companies-2026, ranking #1 in Sustainability. We have also been named to TIME's https://www.linkedin.com/company/time/ list of the 100 Most Influential Companies of 2025 https://time.com/collections/time100-companies-2025/7289577/pano-ai/ and recognized by MIT Technology Review https://www.technologyreview.com/2024/10/01/1104375/2024-climate-tech-companies-pano-ai-fire-detecting-ai/as one of the top climate technology companies to watch. Backed by $89 million in funding https://techcrunch-com.cdn.ampproject.org/c/s/techcrunch.com/2023/07/10/pano-series-a-extension/amp/ from leading investors including Giant Ventures, Liberty Mutual Ventures, Tokio Marine Future Fund, Congruent Ventures, Initialized Capital, Salesforce Ventures, and T-Mobile Ventures, we're building technology that helps communities around the world become more resilient to wildfire. Learn more at www.pano.ai http://www.pano.ai. THE ROLE Pano AI seeks an Analytics Engineer to bring dedicated data and analytics support to our Ops team, during a period of rapid growth in our human review operations. You will be a technically strong, curious professional who is as comfortable digging into a messy SQL query as you are sitting with an agent to understand how they actually work a case — and who takes pride in turning ad hoc investigation into durable, trustworthy tooling. As Pano scales its wildfire detection network and brings on additional review vendors, the volume and complexity of the data Ops depends on is growing quickly. This role will give Ops the dedicated analytics capacity it needs to catch data quality issues early, keep vendor performance reporting accurate as operations evolve, and build the forecasting tools that keep staffing ahead of demand. You will own the dbt models, SQL-powered Metabase dashboards, and tools that both individual contributors and leadership use every day as real operational infrastructure. You will work with our existing Analytics stack to implement end-to-end solutions consisting of importing data from a third party, modeling that data through dbt, and building Metabase dashboards using SQL. This is a role for someone who wants to live in the team's real-world processes — understanding how Ops actually operates day to day — rather than one who only interacts with the business from behind a query editor. WHAT YOU'LL DO - Own the dbt models, Metabase dashboards, and self-serve tools that ICs and leadership rely on daily to do their jobs and check KPIs - Investigate performance differences across vendors and time periods to surface trends and gaps that inform operational decisions - Catch data quality issues in core reporting tables before they mislead decisions, and implement a fix whether that fix requires a change to underlying dbt models the tooling built on tope of those models - Perform root-cause analysis of anomalies in vendor and agent performance data using a rigorous, hypothesis-driven approach - Keep metric definitions consistent as Ops scales across multiple vendors, and proactively catch broken or misleading metrics before they reach a decision-maker - Forecast staffing needs by analy