ClickUp06/10/2026
Инженер бизнес-систем
Salary not specified
MARKET
15,667 ₽median for this role
Data Engineer · 11 jobs with disclosed pay
10,833half of the offers: 14,166–16,81220,833
The employer didn't disclose pay — compare with the market yourself.
Полная занятостьУдалёнка
Responsibilities
- 01Design and build AI-powered automations and agentic workflows across the GTM tech stack
- 02Develop and deploy ClickUp Super Agents and LLM-based automations for tasks like deal data enrichment and quote generation
- 03Architect and implement MCP integrations for intelligent, event-driven actions
- 04Explore and evaluate emerging AI capabilities for GTM business systems use cases
- 05Build reusable AI templates and automation patterns for the GTM Engineering team
- 06Build and maintain integrations across Salesforce, NetSuite, Workato, MuleSoft, and other GTM platforms
- 07Own end-to-end integration patterns for critical business flows like quote-to-cash
- 08Design data flows and transformation logic to keep business data accurate and consistent
- 09Build internal tooling and low-code/no-code solutions using platforms like Retool
- 10Write automation scripts and data transformation logic in Python, JavaScript, or Apex
- 11Utilize iPaaS platforms like Zapier and Workato to orchestrate cross-system workflows
- 12Monitor health and performance of automations and integrations
- 13Conduct root-cause analysis of integration failures and drive durable fixes
- 14Maintain runbooks and operational documentation
- 15Partner with Sales, Revenue Operations, Finance, and Customer Success stakeholders
- 16Work with GTM Systems Engineering, DevOps, and BSA teammates on architecture decisions
Requirements
- 013–5+ years in a business systems engineering, systems administration, or integration engineering role
- 02Demonstrated experience building and shipping automations or integrations that delivered measurable business value
- 03Hands-on experience with Salesforce and at least one ERP platform (NetSuite strongly preferred)
- 04Experience deploying AI or LLM-powered automations in a production business systems context or a clear trajectory toward it