ABOUT OUTMARKET Outmarket is the AI platform for insurance, trusted by more than 250 brokerages to run the work their business depends on. Commercial insurance still runs on dense documents and slow, manual workflows, and that is exactly what we automate: quote comparisons, coverage gap and tower analysis, policy review, and proposal generation, all grounded in our customers’ own data and source-cited so teams can trust the output. The impact is concrete. Teams save 12 to 15 hours per person every week, cut errors by roughly 65 percent, and win more business, all on infrastructure that is SOC 2 Type II certified, single-tenant, and never used to train AI models. We are an AI-first company in both what we build and how we work, shipping quickly and in close partnership with the agencies that rely on us. WHAT YOU’LL GET A high-impact role with ownership from day one. Competitive compensation and meaningful equity. Direct collaboration with founders and real users. Remote-first flexibility. The opportunity to help build an AI-native product from the ground up. ABOUT THE ROLE We are hiring a Senior Data Engineer to own the architecture of our data platform end to end, spanning ingestion, transformation, and the analytical serving layer that powers insights and AI across every customer. You will set the standards for how we model and operate data at scale. WHY THIS ROLE Own the architecture of the data plane the whole product depends on. Solve hard, high-value problems with messy multi-tenant insurance data. Set data engineering standards and mentor the team. WHAT YOU’LL DO Architect ingestion and transformation pipelines (bronze → silver → fact) across many customers. Own multi-tenant data modeling and performance/cost across Postgres and ClickHouse. Define the standards for dataset configuration, KPIs, and reconciliation that keep data trustworthy. Build reliable, observable orchestration and lead data quality strategy. Mentor data and product engineers and review high-impact data work. WHAT WE’RE LOOKING FOR 5+ years in data engineering, including pipeline and analytical-data architecture. Deep SQL and Python, strong Postgres, and hands-on columnar-store experience (ClickHouse or similar). Experience with orchestration (Temporal, Airflow, Dagster) and large-scale data operability. Track record of setting standards and leading data work in a fast-moving environment. BONUS IF YOU HAVE Multi-tenant SaaS data experience. Insurance, fintech, or other regulated/document-heavy domain experience.