Top Tech Jobs & Startup Jobs in Seattle, WA

Analyze acquisition data and guide marketing strategy, budget allocation, channel optimization, and growth decisions. Design incrementality experiments, develop marketing mix and allocation models, define acquisition metrics, identify new growth opportunities, and improve web conversion. Partner with Marketing, Engineering, Finance, Design, and User Research to translate statistical and machine learning insights into measurable business outcomes across paid, organic, consumer, and enterprise channels.

Build and maintain Databricks data pipelines and reusable models for Go product analytics. Define metrics, improve event logging, connect product usage with customer data, and support adoption and growth analysis. Ensure data quality through testing, monitoring, troubleshooting, and documentation. Optimize pipeline performance and costs while collaborating with Product, Engineering, and Data Science. Contribute dashboards and analyses that support product and business decisions.

Embedded Data Scientist for Superhuman Mail, partnering with product, growth, engineering, and design teams to guide roadmap decisions. Responsibilities include defining product metrics, designing experiments, applying causal inference and machine learning, measuring AI feature quality, analyzing activation and retention, identifying growth and conversion drivers, and communicating insights to stakeholders. The role requires strong Python, SQL, experimentation, statistics, and cross-functional influence skills.

Build and own scalable finance and revenue data pipelines, models, and datasets supporting ARR, NRR, bookings, billing, and revenue attribution. Ensure data quality, reliability, monitoring, reconciliation, and self-service access while partnering with Finance, Revenue Operations, Analytics, Product, and Engineering.

Design, build, and operate large-scale ETL pipelines, data lakes, and data platforms processing billions of daily events. Own data quality, freshness, reliability, monitoring, and observability for foundational datasets. Develop self-service ETL frameworks and tooling, contribute to architecture and technical strategy, and partner with product, engineering, machine learning, data science, and leadership teams to deliver scalable data solutions.

Build and lead scalable data governance systems across the data platform, including privacy policy enforcement, metadata and lineage management, data security, regulatory compliance, and purpose-driven access. Architect reliable systems for high-volume data environments, shape technical strategy and roadmaps, collaborate with Privacy, Legal, Security, and Trust teams, and mentor engineers across backend infrastructure and data engineering.

Own the iOS mobile roadmap and technical strategy for Superhuman Mail. Lead high-impact, cross-team engineering initiatives; define the mobile platform’s architecture, technical foundations, and one-to-two-year investment roadmap. Partner with product and engineering leadership on strategy and execution, mentor senior engineers, drive cross-functional alignment, and improve team delivery through AI-native development practices while maintaining high-quality user experiences.

The Software Engineer will enhance the structured data storage layer in Superhuman Docs, ensuring database reliability, performance, and correct data handling under varying workloads. Responsibilities include improving table management, server-side query planning, and collaborating on formula and sync processes.

Lead product management for Superhuman's admin console, enhancing the buyer journey and streamlining admin experiences for enterprises, ensuring security and compliance.

As a Full-Stack Engineer at Superhuman, you will develop core product features, infrastructure, and collaborate with teams to enhance user experience, focusing on both front-end and back-end services.