Remote Data Integration Engineer

Stelloagents; Northern (KY); Hybrid; USD 100,000 - 140,000; Full time

Job summary

Stello, an AI transformation firm, is seeking a Data Engineer on Integrations for a fully remote role in the United States. You will connect our AI agents to client systems, build connectors to CRMs/ERPs, and design real-time or scheduled data pipelines with robust error handling to ensure reliable data flows.

You’ll work directly with client teams to understand systems, map data into clean models, and validate outputs, with a focus on reliability and safe data practices.

Qualifications

• 3+ years building production data pipelines or integrations that people depended on.
• Strong SQL, and strong Python or TypeScript.
• Experience with third-party APIs, webhooks, OAuth, and rate limits.
• You design for failure: retries, idempotency, and backfills.
• You use coding agents every day, and you review their output carefully.
• You can learn an unfamiliar business and turn its requirements into working software.
• You are comfortable with clients, and you explain technical decisions clearly.

Responsibilities

• Work with client IT and operations teams to understand their systems, data, and access rules.
• Build and maintain connectors to CRMs, ERPs, help desks, and data warehouses.
• Design pipelines that sync on a schedule or in real time, and recover cleanly from failures.
• Map messy client data into clean models that agents and reports can use.
• Write agent results back into client systems without duplicates or data loss.
• Build tests and monitoring, so a broken sync is found before the client finds it.
• Explain technical options and tradeoffs directly to the client.

Skills

SQL

Python/TypeScript

APIs

Data pipelines

ETL

Problem solving

Job description

Stello, an AI transformation firm, is seeking a Data Engineer on Integrations for a fully remote role in the United States. You will connect our AI agents to client systems, build connectors to CRMs/ERPs, and design real-time or scheduled data pipelines with robust error handling to ensure reliable data flows.

You’ll work directly with client teams to understand systems, map data into clean models, and validate outputs, with a focus on reliability and safe data practices.