The Role
You are the technical bridge between Terra's platform and our highest-value customers. You embed directly with their engineering and product teams to architect, integrate, and optimize their use of Terra's health data infrastructure.
This is not support. This is not consulting. You are an engineer who ships — the difference is that what you ship lives inside the customer's stack, powered by ours.
Day-to-day, you will:
Design integration architectures for complex health data use cases — determining which Terra endpoints, webhook configurations, and data models map to the customer's product requirements.
Write production code in the customer's environment: building webhook consumers, data transformation layers, authentication flows, and retry logic against Terra's API.
Debug across the full stack — from a Garmin watch failing to sync, to a webhook payload arriving with unexpected schema, to a customer's data pipeline dropping events.
Own the technical relationship with 3–5 strategic accounts simultaneously, serving as their dedicated Terra expert from pre-sales scoping through production go-live and beyond.
Translate field learnings into product — when you see three customers struggling with the same edge case in sleep data normalization, you don't just fix it for them; you work with our engineering team to fix it in the platform.
Build reference implementations, SDKs, and sample apps that make Terra's API easier for every developer, not just your accounts.
Scope and qualify technical requirements during the sales cycle — determining whether a prospect's use case fits Terra's data model, estimating API call volumes, and defining integration timelines.
What you'll work on
These are real problems our customers bring to us. As an FDE at Terra, you'd own the technical delivery:
AI & Personalized Health
An AI lab wants to ingest continuous heart rate, HRV, sleep stages, and activity data from 200K+ users across multiple wearable brands through Terra's unified schema — to power real-time personalized wellness recommendations. You architect the data pipeline: webhook ingestion, event deduplication, backfill strategy for historical data, and rate limiting to stay within their processing capacity.
A conversational health AI needs access to blood biomarkers (glucose, cortisol, cholesterol) alongside wearable data, all normalized and delivered via a single webhook. You design the integration that merges Terra's wearable and blood lab data streams into one coherent user profile.
Insurance & Underwriting
An insurer wants to use real-time biometric data (resting heart rate trends, VO2 max estimates, sleep consistency scores) to offer dynamic premium pricing. You scope the data sources, define the consent flow using Terra's authentication widget, and build the data delivery pipeline that feeds their actuarial models — while ensuring HIPAA and GDPR compliance.
Clinical Research & Digital Health
A clinical research platform needs longitudinal wearable data from a 10,000-participant study across Fitbit, Garmin, and Apple Health. Different devices report different metrics at different cadences. You configure Terra's integrations, build the normalization layer that maps device-specific quirks into a unified research dataset, and handle the edge cases: what happens when a participant switches devices mid-study, or when a data provider pushes a breaking API change.
Fitness & Consumer Apps
A fitness platform with 500K users wants to migrate from maintaining 15 separate wearable integrations to Terra's single API. You plan the migration: mapping their existing data models to Terra's schema, designing the cutover strategy, and building the webhook consumer that replaces their legacy polling architecture. Zero downtime. No data loss.
Upstream Data Supplier Onboarding
A wearable company wants to become a data supplier on Terra's platform — making their data available to Terra's downstream developer and AI ecosystem. You lead the technical onboarding: validating their data format against Terra's schema requirements, configuring consent flows, setting up data quality monitoring, and scoping which downstream developers get access to what.
Must-Haves
3+ years building software, with direct experience designing and consuming REST APIs at scale.
You've owned integrations end-to-end: auth flows (OAuth 2.0, API keys), webhook architectures, error handling, retry logic, idempotency.
Strong in Python or JavaScript/TypeScript — you can prototype a webhook consumer, build an SDK wrapper, or debug a customer's data pipeline in the same afternoon.
You've worked directly with customers or partners in a technical capacity — you know how to translate "our data looks wrong" into a root cause and a fix.
You can context-switch between five different customer architectures in a week without losing depth on any of them.
You communicate clearly and concisely with both engineering teams and non-technical stakeholders — executives, product managers, compliance teams.
Strong Signals
Experience with health, fitness, or biomedical data — you know what HRV is, why sleep staging is hard, and what makes wearable data noisy.
Familiarity with health data standards and compliance: HIPAA, GDPR, FHIR, HL7.
Background in developer tools, platform engineering, or API-first products.
You've worked at or with companies in the wearables, digital health, or health AI space.
Experience building data pipelines that handle real-time streaming and batch backfill at scale.
You've contributed to developer documentation, sample code, or open-source SDKs.
Big Plus
You are an athlete. You train, you compete, you push limits — or at the very least, you are obsessed with quantifying your own data. The discipline, ambition, and courage it takes to show up every day and get better is the same energy we run on. If you understand the data because you live it, you'll build a better product.