The Solutions Architect will lead technical onboarding, design custom integrations, and manage data orchestration for global clients. They will also serve as a product expert, providing training and resolving complex technical issues to ensure long-term client success.
The Implementation Manager acts as the primary project lead for launching new clients, ensuring successful platform adoption and campaign execution. They collaborate with internal technical teams and clients to define goals, manage project timelines, and drive measurable value through the company's software.
Design, build, and maintain end-to-end multi-source ELT pipelines while optimizing for costs and data service level agreements. Collaborate with cross-functional teams to curate event data and deliver reliable data products that drive business decisions.
The Implementation Manager acts as the primary project lead for launching new clients, ensuring successful platform adoption and goal achievement. They design custom technical solutions and collaborate with internal teams to drive measurable value through the company's AI and personalization products.
You will own the product backlog for the event data pipeline, ensuring efficient ingestion, normalization, and governance of data across the platform. Additionally, you will act as a bridge between commercial teams and data engineering to translate business requirements into actionable technical specifications.
The Client Experience Associate will support the Director-led teams by managing client requirements, executing campaign setups, and preparing reports. They will also handle administrative tasks, including meeting coordination, Salesforce management, and creating presentation materials.
The Principal Technical Product Marketing Manager will own the technical positioning, messaging, and feature-level differentiation of the platform. They will collaborate with product, engineering, and sales teams to create technical sales assets and enablement materials for complex enterprise deals.
The Data Engineer will design, build, and maintain high-volume event streaming pipelines and analytical data models. They will also develop production services, ensure system observability, and enforce data quality standards across the platform.
You will design and build scalable data ingestion pipelines and backend services to support the organization's unified data platform. Additionally, you will implement monitoring, observability, and data governance practices to ensure high availability and reliability across all data assets.
The role involves deploying commercial-grade AI products and integrating breakthrough innovations into the core AI model suite. You will also be responsible for engineering scalable ML systems and elevating the platform's standards for monitoring and automated testing.
The role involves improving infrastructure tooling and automation to minimize manual work and increase platform performance. You will build and support core applications while monitoring systems for capacity and troubleshooting issues to ensure service reliability.
