Customer-Facing Data Integration Engineer

Talently; Ciudad de México; On-site; MXN 2,242,000 - 3,363,000; Full time

Job summary

QuadSci, a New York-based AI startup, is seeking a Forward Deployed Engineer to join our team. You will collaborate with customer teams to design integrations and productionize data pipelines, APIs, and services that power churn prediction and revenue operations.

You will own end-to-end implementations from discovery to deployment, build Python-based processing systems, and create reusable tooling to scale data flows and developer experience across diverse SaaS platforms.

Qualifications

• 5+ years building production software (backend services, APIs, or data integrations).
• Strong expertise in Python for production systems.
• Hands-on experience with ETL and data transformation pipelines.
• Solid understanding of REST APIs, OAuth/API-key auth, webhooks, and asynchronous background jobs.
• Proven track record of integrating with third-party SaaS platforms.

Responsibilities

• Collaborate with customer technical teams to understand data sources, schemas, and system constraints.
• Own the technical implementation for customer integrations from initial data discovery to production deployment.
• Design and maintain pipelines to ingest, clean, and transform data from diverse sources (APIs, Databases, Events).
• Build Python-based systems for data processing and orchestration, focusing on performance and memory efficiency.
• Develop and maintain REST APIs, services, and workers that expose platform functionality.
• Create shared libraries and internal tooling to support scalable data flows and improve the developer experience

Skills

Python

ETL pipelines

REST APIs

OAuth/API-key

Third-party integrations

Job description

QuadSci, a New York-based AI startup, is seeking a Forward Deployed Engineer to join our team. You will collaborate with customer teams to design integrations and productionize data pipelines, APIs, and services that power churn prediction and revenue operations.

You will own end-to-end implementations from discovery to deployment, build Python-based processing systems, and create reusable tooling to scale data flows and developer experience across diverse SaaS platforms.