Senior Analytics Engineer, Client Engagement

About the role

Sage is on a mission to improve care and quality of life for older adults, starting with those residing in senior living facilities. Falls are the leading cause of injury-related death among adults over 65. And yet, fall prevention and emergency response systems for older adults are archaic and ineffective. At Sage we've built a more modern way of understanding when older adults need help, including methods for residents to alert caregivers when in need of help, and corresponding software for caregivers to triage response. Our company mission is to create a product that our client counterparts love, and this role is a key part of that objective. Sage is a small, tight team of ambitious, multi-disciplinary entrepreneurs. We are a software-enabled, mission-driven company, and are focused only on the problems that are central to achieving that mission. At Sage, we work hard and fast but also know that to build a truly important company, we need to treat our work as a marathon, and not a sprint. The journey matters. About this Role This Senior Analytics Engineer for Client Deployments will be a pivotal technical player in our fast-growing startup. You will focus on new client engagements, prioritizing value creation within the critical first 3-6 months of communities going live. You will act as the technical bridge between our clients, Sage operations teams, and the data architecture that drives our insights. Because on-site context is vital to our success, you should expect up to 25% travel (typically 1-2 weeks at a time maximum) to work directly with clients and ensure seamless deployments.

Responsibilities

• Client Engagement & Scoping: Partner closely with clients and Sage operations teams to scope and define technical requirements for new community deployments.
• Pipeline & Architecture: Build and maintain robust bi-directional data pipelines to ensure seamless, secure data flow between client systems and Sage's infrastructure.
• Custom Analytics & Modeling: Develop custom analyses, data models, and reporting dashboards that drive immediate, measurable value for clients in their first 3-6 months post-launch.

Requirements

• 4-8 years of professional experience in analytics engineering, data engineering, or a closely related technical field.
• Proven track record of designing and building data pipelines, custom analyses, data models, and reporting systems.
• Strong client-facing communication skills with experience scoping complex technical requirements alongside both technical and non-technical stakeholders.
• Ability and willingness to travel up to 25% of the time (in 1-2 week increments).
• Experience working in a fast-paced B2B startup environment or deploying software to external enterprise clients.
• Background working with healthcare, senior living, or health-tech data domains.
• Benefits and Pay
• EEO Statement

Benefits

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