A genuinely hands-on player-coach data/application architect who can look at Nickel's current data architecture, critically assess what's solid vs. wrong, and lead the org out of the gaps — while writing code, not just diagramming. The team is small and everyone's an IC (no architect-designs / developers-implement split), so this person must be "not just casually hands-on" but able to lead through the work. The application layer itself is deliberately simple (a big-button patient mobile app, a glanceable physician dashboard) — the hard part is underneath: getting four-to-five very different data categories into the right place and format and making them coherent — time-series data, raw blobs/objects (non-queryable), EHR/EMR-formatted stores (Epic/Oracle Health/Athena, via different aggregators and pipelines even from the same source), and a knowledge graph (separate, not directly queryable) — plus deduplication, filtering, and reconciliation across them.
Because it's PHI, traceability is non-negotiable: every layer of data access, consumption, and interpretation (including anything an AI agent touches) must be fully logged, auditable, and traceable end to end — so a regulated-industry background (healthcare or finance/audit) is highly valued. First ~30 days is heavy critical assessment: "here's what I'm seeing, here's what should work, here's what to change," then iterating. Natural 12–18-month progression is toward working with the CTO to define the next leg — a quasi-CTO-track seat, though not required.
What You'll Own
- Critically assess and re-shape the current data architecture; decide what to keep, kill, build, buy, or open-source
- Architect coherent handling across time-series, blob/object, EHR/EMR, and knowledge-graph data — ingestion, format, relation, dedup/filtering
- Multi-source EHR integration breadth (Epic, Oracle Health, Athena) via aggregators and differing pipelines — not single-source depth
- End-to-end PHI traceability/auditability across every data-access and interpretation layer
- Licensing/policy calls on components (e.g., no AGPL/GPL); middleware, messaging/streaming (Kafka-type), security per layer, end-user data representation
- Hands-on implementation as a player-coach; help surface gaps for the CTO
Requirements
- Proven enterprise architecture across many moving parts — DB, middleware, messaging/streaming (Kafka-type event handling), security per layer, end-user visualization
- Genuinely hands-on player-coach — codes and leads; not a big-corp architect who's gone hands-off
- Broad multi-source data view (not deep-in-one-tool, e.g., Epic-only) — comfortable reconciling conflicting/duplicated data across heterogeneous sources
- Fluent across time-series, blob/object stores, EHR/EMR data, and knowledge graphs
- Strong "build vs. buy vs. open-source" judgment, incl. license awareness
Execution and Ownership
- Startup-bred — sweet spot is people out of startups (big-enterprise-only usually isn't hands-on enough to lead a small team)
- Conflict resolution / stakeholder management — will be challenged by (and must challenge) eng, GTM, and hardware; can convince without authority
- Title-agnostic IC mindset — "I don't care about title, I just want to work"
Background
- Regulated-industry data experience strongly valued — healthcare (PHI) or finance / any audited environment (traceability instincts transfer)
- Healthcare helps but isn't required; single-EHR specialists (e.g., pure Epic) are a weaker fit than broad-source generalists
Who Will Thrive Here
- A hands-on architect from startups who leads through code, not title
- Someone energized by messy, heterogeneous, multi-source data and PHI-grade traceability
- A diplomat who can resolve architecture tension across a small multicultural, cross-functional team
- Regulated-industry (health or finance/audit) background with broad data breadth
- On a genuine CTO-track trajectory but happy as a title-less IC today
No benefits listed yet.