Data & Integrations Engineer

ABOUT MUDANZA

Memory that serves the relationship.

Mudanza is an early-stage advisory platform and governed memory layer for wealth management. We are building around a simple idea: what a firm learns about its clients should carry forward, with the context and evidence that make it useful.

A client’s priorities live across conversations, notes, documents, and separate systems. Our direction brings that knowledge into one living record, connecting it to planning and the work that follows. AI should help people prepare, understand, and follow through while preserving human judgment.

Our five co-founders bring experience in advisory practices, capital markets, technology consulting, enterprise data and AI, and building businesses. We are still early: these roles will help shape both the product and the way we build it.

Why this role matters

Advisory firms work across CRM, custodial, planning, reporting, document, and communication systems. Each has its own identifiers, update patterns, and gaps. Mudanza’s shared memory depends on bringing the right information together without losing ownership or provenance. You will build the integration and data foundations that let an advisor trust the record, see what has changed, and recognize what still needs reconciliation.

The scope of your role

You will work with the co-founders, product and AI engineers, and implementation lead. The work spans connector design, customer onboarding, data modeling, operations, and vendor troubleshooting. Success is a repeatable integration that can be monitored and recovered, not a one-time import that appears to work. Priorities will follow real customer workflows and available vendor access rather than a speculative catalog of logos.

What you’ll own

• Design secure connectors and ingestion jobs for APIs, webhooks, and authorized file imports, including authentication renewal, pagination, rate limits, and schema changes.
• Model people, households, accounts, relationships, activities, and source identifiers. Make entity matching explainable and route ambiguous matches for review.
• Build idempotent processing, incremental synchronization, reconciliation, and controlled replay. Handle late-arriving events, duplicate payloads, deletions, and partial outages.
• Preserve source attribution, effective dates, freshness, and transformation history so product and AI features can distinguish a known fact from an outdated or incomplete record.
• Enforce tenant boundaries, least-privilege access, and secure secret handling throughout connectors, storage, logs, and support tooling.
• Create migration validation and exception reports that implementation teams can use to explain what was imported, rejected, or left unresolved.
• Own connector health metrics, alerting, runbooks, and recovery paths. Document vendor constraints and prevent silent failures from becoming misleading product answers.

What you bring

• Production experience integrating third-party systems and owning their reliability after launch.
• Strong SQL and data-modeling skills, plus fluency in a backend language such as TypeScript or Python.
• Practical knowledge of OAuth, API authentication, queues, retries, consistency, and idempotency.
• Experience diagnosing data-quality problems such as broken joins, duplicates, missing records, and changes in source schemas.
• The ability to explain reconciliation results and tradeoffs clearly to engineering and customer-facing teams.

Especially useful experience

These are helpful additions, not a checklist you must complete.

• Wealth management, CRM, custodial, portfolio, or communication-system integrations.
• Azure data services, event-driven architectures, migration tooling, and sensitive-data retention controls.

Your first 90 days

A starting framework for the role; we’ll shape the sequence around product and customer priorities.

1. Days 1–30

   Map a priority source, its access model, data contract, and known quality gaps with the implementation team.

2. Days 31–60

   Deliver a recoverable ingestion path with reconciliation, monitoring, and explicit handling of unresolved records.

3. Days 61–90

   Document an operational playbook and demonstrate repeatable onboarding or recovery without bespoke manual repair.

How we approach the work

Start with the person and the problem. Make a small, complete improvement. Keep sources and assumptions visible. Test the important failure cases, and follow the work through to its actual use. We value clear writing, thoughtful disagreement, and the ability to change direction when the evidence changes.

In an early team, ownership includes the edges: documenting a decision, helping a teammate, investigating an issue, and being honest about what is ready and what is still being built.