Embedded Python Data & Automation Engineer

Embedded Python Data & Automation Engineer – Data Pipelines, APIs & Automation | Remote

Position Type: Full-Time, Remote
Working Hours: Meaningful Overlap with U.S. Business Hours
About the Role

At Pavago , one of our clients is hiring an experienced Embedded Python Data & Automation Engineer to take ownership of an existing Python environment, maintain production systems, improve data pipelines and automations, and develop practical internal tools and integrations.

This is a hands-on engineering role with an important initial focus on system transition and knowledge transfer . You’ll work closely with a departing programmer to understand the existing Python codebase, production workflows, integrations, dependencies, and automations before assuming ownership of the environment.

As the transition progresses, your focus will shift toward improving reliability, reducing technical debt, expanding automations, strengthening integrations, and building new internal tools based on business needs.

If you’re comfortable inheriting an existing codebase, troubleshooting production systems, and gradually making them more reliable and maintainable, this role is a strong fit.
What You’ll Own
System Transition & Technical Ownership

- Shadow the departing programmer and absorb critical system knowledge

- Take ownership of the existing Python codebase

- Understand existing:

- Applications

- Data pipelines

- Scheduled automations

- APIs and integrations

- Dependencies

- Deployment workflows

- Identify undocumented processes and system dependencies

- Document critical knowledge throughout the handover process

- Develop sufficient technical context to independently maintain and extend the environment

- Ensure a smooth transition with minimal disruption to production systems

Production Support & Maintenance

- Troubleshoot live production issues

- Maintain existing applications, scripts, and automated processes

- Investigate failures and unexpected system behavior

- Identify root causes and implement reliable fixes

- Monitor system stability and recurring technical issues

- Raise technical risks early

- Prioritize reliability when modifying existing production systems

Data Pipelines & Automation

- Maintain, debug, and improve production data pipelines

- Monitor scheduled automations and investigate failures

- Improve pipeline reliability and maintainability

- Build new automations based on business requirements

- Reduce repetitive manual processes through practical engineering solutions

- Identify opportunities to improve existing automated workflows

- Ensure critical jobs and pipelines continue operating reliably

APIs & Integrations

- Maintain and extend existing APIs and third-party integrations

- Work with:

- APIs

- Authentication flows

- Webhooks

- Third-party services

- Troubleshoot integration and authentication issues

- Maintain reliable data exchange between systems

- Extend integrations as business requirements evolve

- Document integration logic and dependencies

Technical Debt & System Reliability

- Identify:

- Fragile systems

- Undocumented dependencies

- Technical risks

- Maintenance bottlenecks

- Prioritize technical debt based on operational impact

- Refactor and improve existing systems over time

- Reduce unnecessary complexity where appropriate

- Strengthen system reliability without disrupting production

- Flag areas where existing architecture could create future operational risk

Documentation & Knowledge Management

- Create and maintain:

- Technical documentation

- Workflow diagrams

- Dependency maps

- Operating procedures

- Document systems as you learn and modify them

- Keep technical documentation current as workflows evolve

- Ensure critical system knowledge is not dependent on a single individual

- Make troubleshooting and future development easier through clear documentation

Internal Tooling & Development

- Build practical automation tools