Customer Data Engineer (LATAM) - 20629

Role: Customer Data Engineer
Priority Location: Latin America
Working Hours: Full-time (Remote)
Salary: $38,000–$68,000 USD/year
Employment Type: Full-time | Remote

A fast-growing fintech SaaS company building a decision intelligence platform for independent wealth management firms and Registered Investment Advisors (RIAs). The platform helps financial professionals improve portfolio risk analysis, compliance workflows, and advisor productivity. Operating in a large and rapidly growing market, the company has established strong product-market fit and continues to scale with a globally distributed team.

The Customer Data Engineer sits at the intersection of Engineering and Customer Success, playing a vital role in investigating and resolving customer data issues, identifying root causes, and implementing durable fixes. This individual will troubleshoot data problems using Python, Django, SQL, and ETL processes, ensuring high data reliability while effectively communicating technical concepts to both technical and non-technical stakeholders.

Working cross-functionally with Engineering, Integrations, and Customer Support, the Customer Data Engineer will balance technical debugging with proactive customer communication. The ideal candidate is both technically strong and customer-oriented—someone who thrives on solving production data issues while delivering an exceptional experience across the customer lifecycle.

• →Investigate customer data issues, perform root-cause analysis, and execute durable technical fixes.
• →Reconcile and safely correct customer data and CMS records in production environments.
• →Troubleshoot data pipelines and optimize ETL processes to improve long-term system reliability.
• →Build internal diagnostic and troubleshooting tools to streamline incident management.
• →Collaborate closely with Customer Support to provide timely, accurate issue resolution.
• →Escalate systemic data pipeline and architectural issues to the Integrations Data Engineer as appropriate.
• →Partner with core Engineering teams to continuously improve platform data quality and reliability.
• →Communicate technical findings, updates, and resolutions clearly to non-technical stakeholders and clients.

• Strong SQL skills with proven experience troubleshooting production data.
• Intermediate proficiency with Python and the Django framework.
• Direct experience investigating and resolving complex, customer-facing technical issues.
• Hands-on experience with ETL pipelines, data transformations, and building diagnostic tools is preferred.
• Background in fintech, SaaS, or data-intensive applications is a strong plus.
• Familiarity with customer support workflows and production incident management.
• Strong analytical, debugging, and problem-solving skills with a high attention to detail.
• Excellent written and verbal communication skills with a customer-focused mindset.

• Customer data issues are resolved quickly, accurately, and with minimal friction.
• Root causes are effectively identified and long-term pipeline fixes are implemented.
• Data quality and ETL reliability continuously improve over time.
• Transparent communication and strong cross-functional collaboration result in an outstanding customer experience.