Top Tech Jobs & Startup Jobs in Seattle, WA

Target and break into large enterprise accounts (>$100M software spend) using outbound prospecting (cold calls, emails, LinkedIn) to generate meetings with procurement leaders. Use modern sales tools, collaborate with sales leadership and enablement, refine messaging, and develop toward full end-to-end sales responsibility.

Lead modernization and scaling of YipitData’s AWS cloud infrastructure, Kubernetes platform, Terraform ecosystem, SRE, DevOps, and developer experience. Manage a global player-coach team, establish reliability and disaster-recovery practices, improve platform adoption and engineering velocity, create sustainable 24/7 operations, and optimize cloud costs while maintaining reliability.

Advises managers and senior leaders globally on organizational design, workforce planning, talent strategy, leadership development, performance, compensation, succession, employee relations, and organizational change. Leads scalable People programs, identifies talent risks, supports high-performance culture, and uses data, business context, AI, and technology to improve decision-making and operational effectiveness.

Leads the emerging sector insights team, owning product strategy and roadmaps for key categories, managing and developing insights analysts, and driving sector commercial success through collaboration on upsell and renewal opportunities. The role combines market research, client service, data analysis, cross-functional collaboration, and thought leadership. It is remote-friendly within the United States and requires East or West Coast work hours.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.

Own Kepler’s transaction data feed end-to-end, ensuring accuracy, improving methodologies, developing QA frameworks, solving complex analytical problems, and prototyping enhancements. Analyze massive datasets, automate workflows with AI, evaluate client-facing AI outputs, address high-complexity customer questions, and collaborate with Research, Product, Data Science, and Engineering teams.

Conduct outbound prospecting through cold calls, emails, LinkedIn, and other channels; qualify inbound and marketing-qualified leads; communicate product value; collaborate with Sales, Product, GTM Engineering, and Marketing; map decision-makers and personas; and use sales technology to expand markets and generate new business.

Own YipitAgent’s product-led growth motion across acquisition, trial activation, engagement, conversion, retention, and re-engagement. Optimize SEO/AEO, onboarding, in-product education, lifecycle communications, pricing, packaging, and trial experiences. Use customer research, behavioral data, funnel metrics, cohorts, and experimentation to identify growth opportunities. Partner with product, design, engineering, data, marketing, sales, and customer teams to launch, measure, and iterate on experiences that increase trials, active usage, and paid conversion.

Own high-impact data products, ingestion pipelines, and granular data feeds end to end. Analyze massive datasets to answer client and stakeholder questions, ensure data accuracy, and derive actionable insights. Improve products and pipelines by developing methodologies, scaling third-party datasets, and creating data modules. The role requires clear communication, attention to detail, methodical problem solving, prioritization, experimentation, and strong ownership. Training includes SQL, PySpark, Python fundamentals, and internal tools.

Drive discovery, development, commercialization, and improvement of alternative data products. Evaluate and source datasets, collaborate with Partnerships and Revenue teams, conduct client research, shape product strategy, communicate roadmaps, and potentially build and manage a Product Development Analyst team. The role focuses on expanding revenue and client engagement through innovative data experiences and requires strong understanding of financial client needs and data technology.