The Account Executive II role at WorkWave focuses on small Lawn service businesses, managing the sales cycle, conducting demos, and exceeding sales quotas.

Drive sales by supporting Account Executives and Account Managers with technical positioning of Wavelytics software, ensuring customer understanding and leading sales pursuits when necessary.

The Enterprise Account Executive will manage high-stakes sales cycles, consult with C-level decision-makers, and drive enterprise SaaS solutions while maintaining strong cross-functional relationships.

The Senior Data Analytics Engineer will own the data ecosystem, manage pipelines, support AI/ML initiatives, and translate business goals into technical requirements. They will also ensure data reliability and optimize performance across analytics platforms.

The Manager, Web Strategy will oversee and enhance the digital portfolio, managing website strategies, user experiences, and analytics. Responsibilities include leading a team, executing web strategies aligned with business goals, and optimizing content for engagement and conversion.

The Principal Financial Analyst will partner with business units, drive financial modeling, lead planning processes, and prepare financial insights and reports to support strategic decisions.

The Communications & Brand Strategist will execute communication strategies, create content, manage media relations, and enhance internal messaging. They will strengthen brand reputation and drive employee engagement, collaborating with teams to align marketing objectives.

The Sales Operations Analyst will analyze sales data, create reports, support forecasting, and collaborate with cross-functional teams to optimize revenue operations.

The Director of Revenue Operations will lead strategic sales operations, manage forecasting, pipeline analytics, and oversee the global operations team. This role focuses on improving operational excellence and collaborating with Sales and Finance departments.

Lead design and implementation of scalable data pipelines and ML feature flows, own data platform architecture, ensure governance and observability, optimize cloud infrastructure, mentor engineers, and collaborate with product and customer stakeholders to deliver AI-enabled data products.