About the Company

A Series A decision-intelligence platform for independent wealth management (founded 2017), serving registered investment advisors with tools spanning portfolio risk analytics, compliance workflows, and advisor productivity. Operating in a $100B addressable market with strong product-market fit among mid-market and enterprise RIA clients. Growth-stage, under 100 employees, running on EOS with a lean, accountable team working directly with the CEO, Head of Sales, and Head of Customer Success.

About the Role

This is the support-focused half of the company's customer-data work, partnering closely with a separate, build-focused Integrations Data Engineer. The Customer Data Engineer investigates and resolves customer data issues to root cause, reconciles and safely corrects records in the CMS, builds diagnostic and troubleshooting tooling that speeds triage, improves ETL for durable fixes, and communicates status back through Support to customers. Systemic pipeline and data-model problems are handed off to the Integrations Data Engineer; knowing where that line sits is part of the job.

Crucially, this role sits at the bridge between Engineering and Support. It's for someone who genuinely codes (intermediate Python/Django, strong SQL) but is also customer-focused and can explain complex technical problems plainly to non-technical people. A pure backend engineer with no interest in support or customer communication is explicitly the wrong fit.

What You'll Own

• Investigating and resolving customer data issues to the root cause
• Reconciling and safely correcting records in the CMS
• Building diagnostic and troubleshooting tooling that speeds triage
• Improving ETL for durable, systemic fixes, and handing deeper pipeline/model issues to the Integrations Data Engineer
• Communicating status and resolution back through Support to customers

Must-Have (hard)

1. Intermediate Python/Django
2. Strong SQL with data reconciliation and validation
3. Systematic troubleshooting and root-cause analysis
4. Strong English, able to explain complex technical issues clearly to non-technical people
5. Customer-focused, comfortable being the bridge between Engineering and Support
6. Experience resolving production data issues to root cause

Nice-to-Have

• Support / success / implementation-engineering background
• SaaS or fintech, especially wealth management or financial data
• Custodial feeds, CRM integrations, or market-data providers
• Experience building internal diagnostic tooling
• Monitoring / error-tracking tools
• Financial / securities data familiarity

Details

Employment: Full-Time  |  Location: Remote — LATAM  |  Experience: 3+ years
Compensation: $3,000–$5,000 per month. No visa sponsorship.