Senior Full Stack Engineer - Data & Analytics

Job Title: Senior Full Stack Engineer - Data & Analytics

Prompt is a mission-driven startup looking for an experienced Senior Full Stack Software Engineer to help push forward an ambitious set of data and analytics initiatives in healthcare, with a particular emphasis on making data actionable to drive decision making.

Prompt delivers highly automated and modern B2B enterprise software to rehab therapy businesses, their teams, and most importantly the patients they serve. We've established ourselves as the go-to platform in the space and are rapidly growing our market share by delivering software people love.

As we scale, data is becoming increasingly central to how we make decisions and drive improvement. We're looking for a Senior Full Stack Engineer who is a true generalist — comfortable moving between application code, data pipelines, and the user-facing surfaces that make data useful — and who uses modern AI tooling to move faster and build better. This role will contribute to internal and external facing data and analytics products — helping drive extraordinary outcomes for our clients and their patients while internally driving efficiency and decision-making across Product, Client Success, Growth, and Operations.

This is a high-ownership role focused on iteratively building systems end-to-end, partnering closely with stakeholders, and ensuring our data and analytics products deliver real value.

Why work for Prompt?

Big Challenges: Here at Prompt, we are solving complex and unique problems that have plagued the healthcare industry since the dawn of time.

Talented People: Prompt didn't happen by chance, it's a team of incredibly talented and proven individuals who all made their mark before joining forces to build the greatest software on the planet for rehab therapists.

Healthy Approach: This isn't an investment bank. At Prompt you own your workload and the entire organization takes a liking to smart work (over hard work).

Positive Impact: Prompt helps outpatient rehab organizations treat more patients and deliver better care with less environmental waste. That means less surgery and less narcotic-based pain treatment, all while turning a paper-heavy industry digital.

Responsibilities

Drive Prompt's mission to improve healthcare through high-quality, actionable data and analytics that inform client and internal decision-making

Build full-stack data and analytics features end-to-end — from building the data models, analyzing the data, to the user-facing interfaces that surface insights

Build AI and LLM-powered workflows that accelerate data transformation, analysis, and app development — while maintaining high standards for reliability and maintainability

Own the design, development, and iteration of complex data systems, including the building data transformations, and well-modeled datasets

Develop and ship analytics products and dashboards used by clients and internal teams

Perform exploratory analysis and hypothesis-driven investigations to surface insights and guide product and operational decisions

Influence data engineering team strategy and product architecture for data and analytics surfaces

Partner with stakeholders across the company to understand client and internal workflows, define success criteria, and deliver products that drive improvement

Qualifications

4+ years of software development experience with a focus on full-stack web development and data modeling/analysis

Strong proficiency in Python and SQL for data transformation, analysis, and analytic pipeline development

Experience building backend servers and modern frontend interfaces (React, Vue, or equivalent) for data-rich applications

Demonstrated fluency with modern AI and LLM-powered development tools (code agents, automation frameworks) and a track record of using them to ship higher-quality work faster

Proven ability to work with complex, messy, and evolving data sources and turn them into reliable, well-modeled datasets

Experience designing, building, and operating end-to-end data workflows — from raw data ingestion through transformation, modeling, and downstream analysis