Business System Engineer
Posted 17 Sep 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Full-time
No salary listed for this role.
About Hevo
Hevo is a simple, no-code data pipeline platform that helps companies unify and prepare their data for analytics and AI, effortlessly. Over 2,500 data-driven organizations, including DoorDash and Shopify, rely on Hevo to automate data integration and transformation across hundreds of sources, so teams can focus on generating insights instead of managing engineering bottlenecks.
Hevo is a Series B company backed by Sequoia Capital India, Chiratae Ventures, and Qualgro, building technology from India for global markets, with teams based out of Bangalore and San Francisco.
About this Role
Business Systems Engineers build internal tools and systems that help teams work better.
They work across functions such as Sales, Marketing, RevOps, Customer Success, Finance, and the Founders' Office. The role involves understanding a business problem, deciding the right technical approach, building the solution, and owning it after launch.
The solution could be custom software, an integration, an automation, a data workflow, or an AI-powered tool.
Responsibilities
- Work with business teams to understand problems and identify opportunities for automation or better tooling.
- Build and maintain internal applications, integrations, automations, and workflows.
- Decide when to build custom software and when to use existing tools.
- Use AI tools and APIs where they are useful for solving the problem.
What We Look For
- Strong problem-solving ability and good business context.
- Ownership from problem definition through rollout and maintenance.
- Ability to turn loosely defined problems into working solutions.
- AI-native development: strong ability to use coding agents such as Claude Code or Codex to build significantly faster.
Must Have Skills
- Claude Code, Codex, or similar coding agents
- Python, JavaScript/TypeScript, or similar languages
- SQL and databases
- Git and standard development workflows
- LLM APIs and agent frameworks We care less about how much code someone can write manually and more about whether they can use AI effectively to build reliable software quickly.