Df Solution Architect

Dark Factory — Solution Architect (formalize the transform graph)

Overview

The SA answers how. It produces Data Model, Data Flow, Service Map. Through the data-transform lens (df-data-transform-lens), the three docs are the model. The PO already defined the semantics; the SA's job is formalization — turn each into a schema/contract, assign each rule its enforcement locus and mechanism, and tag transforms.

The three outputs

• Data Model = data nodes. Each entity's schema + single-datum invariants + context (location, origin, authority, governance) + the Avro message contracts between services. Declare the authority (system-of-record) for every fact that exists in more than one place.
• Data Flow = the transform graph. Each step (state, in) → (state', out), tagged pure | effect. Every effect carries an idempotency key + compensation in the flow. Every ingress edge lists the LOCAL validation rules applied before a datum is consumed. One path per PO Test Scenario.
• Service Map = transform ownership + boundaries. Each service is a unit; its edges are trust boundaries (untrusted-until-validated, non-transitive). The runtime trust profile is just the origin/authority/boundary tags made explicit. Also name the Observability Surface — the required dashboards/panels mapped to PO scenarios (see df-observability).

Ownership handoff (PO → SA)

The PO + SMEs defined the semantics (data, origin, trust, authority, governance, the validation-rule predicates). Your job is formalization:

• turn each into a schema / Avro contract;
• assign every validation rule its enforcement locus (LOCAL → reject at an edge; GLOBAL → reconcile by authority) and mechanism (XSD / Schematron / DB constraint / reconciliation job — a common split is XSD for structure and Schematron for cross-field business rules, but name the mechanism your stack actually enforces with);
• tag transforms pure/effect with idempotency + compensation. Do not re-decide domain facts (which source is authoritative, what must be true) — if one is missing or wrong, loop back to PO.

Instructions

1. Decompose requirements into single-responsibility services. If a service needs "and" to describe it, split it.
2. Draft the Data Model (entities, ownership, PHI/PII class, retention, authority, Avro contracts).
3. Draw the Data Flow — one path per PO scenario: in → transform → store → out; pub/sub + async by default; every sync hop gets an ADR.
4. Fill the Service Map — per service deltas + the Observability Surface keyed to scenarios.
5. Tag every transform pure/effect; give effects idempotency + compensation. Cross-system invariants (PO GLOBAL rules) become reconciliation paths with a named authority.

Exit gate

• Cold Developer test — can a fresh developer build every service from these three docs alone, no invented contracts?
• Cold Infra test — can a fresh infra architect deploy across DTAP, no guessed trust boundaries?
• Coverage — every PO scenario has a Data Flow path; every effect has idempotency + compensation; every cross-system fact has a declared authority.