Embedded Python Data & Automation Engineer
- Role
- Data Engineering
- Experience
- Mid
Open to PH only · UTC-8…UTC-5. Set where you work from to check your eligibility.
No BS summary
Mid-level Python engineer (3+ years) focused on data pipelines and automation. Must be located in the Philippines and able to overlap US business hours. Responsible for taking ownership of an existing Python codebase, maintaining production systems, and owning APIs/integrations.
Core skills
Required skills
Required languages
About The Role We are looking for an Embedded Python Data & Automation Engineer to take ownership of an existing Python environment, maintain production systems, improve automations and data pipelines, and develop internal tools and integrations. Key Responsibilities System Transition & Knowledge Absorption: Shadow the departing programmer and take ownership of the existing Python codebase. Production Support & Maintenance: Troubleshoot live issues, maintain existing systems, and ensure system stability. Data Pipelines & Automations: Maintain, debug, and improve data pipelines and scheduled automations. API & Integration Ownership: Maintain and extend APIs, third-party integrations, authentication flows, and webhooks. Technical Debt: Identify fragile systems, undocumented dependencies, and technical risks and improve them over time. Documentation: Create and maintain system documentation, workflow diagrams, dependency maps, and operating procedures. Internal Tooling: Build practical automation tools and internal software based on business needs. Engineering Practices: Use Git, pull requests, automated testing, changelogs, and staged deployments. Required Experience & Skills 3+ years of professional Python experience in a data-focused environment. Experience building or maintaining production data pipelines and automations . Strong experience with APIs, integrations, authentication, and webhooks . Experience working with an existing or legacy codebase . Working knowledge of SQL and relational databases . Familiarity with Git, pull requests, testing, and deployment workflows . Strong written English and technical documentation skills. Ability to work with meaningful overlap with US business hours . Typical Day Your day begins with a check on overnight automations and any open production issues. You spend focused blocks working through the current system — reading existing code, running tests, tracing integrations, and filling in documentation gaps. Early in the engagement, a meaningful portion of your time is in handover sessions with the departing programmer. As the transition matures, that time shifts toward new development: building automations, improving pipeline reliability, or scoping a new internal tool with the client. You communicate primarily over Slack and participate in planning sessions and check-ins that align with US business hours. You raise flags early, document as you go, and push changes through staging rather than directly to production. Interview Process Video Interview Screening Client Interview Offer Stage
What you'll do
- Shadow the departing programmer and take ownership of the existing Python codebase.
- Troubleshoot live issues, maintain existing systems, and ensure system stability.
- Maintain, debug, and improve data pipelines and scheduled automations.
- Maintain and extend APIs, third-party integrations, authentication flows, and webhooks.
- Identify fragile systems, undocumented dependencies, and technical risks and improve them over time.
- Create and maintain system documentation, workflow diagrams, dependency maps, and operating procedures.
- Build practical automation tools and internal software based on business needs.
- Use Git, pull requests, automated testing, changelogs, and staged deployments.
What they require
- 3+ years of professional Python experience in a data-focused environment.
- Experience building or maintaining production data pipelines and automations.
- Strong experience with APIs, integrations, authentication, and webhooks.
- Experience working with an existing or legacy codebase.
- Working knowledge of SQL and relational databases.
- Familiarity with Git, pull requests, testing, and deployment workflows.
- Strong written English and technical documentation skills.
- Ability to work with meaningful overlap with US business hours.
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