Python Automation & Data Engineer API Integrations, ETL Pipelines

I run a small portfolio of digital products and internal business operations. As we've grown, we've accumulated a steady backlog of automation and integration work, data pipelines, scheduled jobs, API connections between our tools, reporting scripts, and lightweight internal dashboards. I'm looking for one reliable Python engineer to work with me on an ongoing basis. Not a one-off hire, someone who gets familiar with our systems and becomes a long-term execution partner. I define the scope and write the specs; you implement, deploy, and keep things running. What the work looks like: Building and maintaining ETL pipelines that pull data from external sources, transform it, and route it to the right destination (databases, reports, downstream APIs) Event-driven and scheduled automation, webhook triggers, cron jobs, polling loops, email-based triggers Connecting our SaaS tools to each other via their APIs (CRM, communication tools, document workflows, cloud storage) Data cleanup, reconciliation, and reporting scripts using Python and SQL Small internal services and admin dashboards Monitoring and maintaining what gets built, this isn't ship-and-forget work Stack we work in: Languages: Python (primary), JavaScript / Node.js where needed Data: PostgreSQL, MS SQL Server, pandas, CSV/Excel processing Automation & orchestration: n8n for simpler glue work, Python services for complex logic Cloud & hosting: AWS (Lambda, API Gateway, S3), Azure, DigitalOcean, depending on the project APIs & auth: REST, OAuth2, webhooks, third-party SaaS integrations DevOps basics: Docker, environment-based secrets management, CI/CD pipelines What I need from you: Strong integration instincts you know how OAuth2 flows work, you handle errors and retries properly, you think about failure modes upfront Clean, production-ready code secrets in env vars, structured logging, failure alerts. Code that runs reliably at 3am without babysitting Careful with sensitive data some workflows touch business and personal records. You understand what that means: no unnecessary third-party surfaces, proper credential scoping Clear communicator I write detailed specs. You read them, ask the right clarifying questions, then build. No disappearing mid-project Reliable availability this is a retainer-style arrangement. Consistency matters more than raw speed Nice to have: Experience with n8n, Make, or Zapier — knowing when to use low-code vs. custom code is a skill Apache Airflow or similar orchestration experience for more complex pipeline work Familiarity with Django or Django REST Framework for any internal tool work Experience handling PII or financial data responsibly How we'll start: The first engagement will be a well-scoped, paid project a real task from our actual backlog with a clear spec. How you handle the implementation, deployment, and any sensitive-data considerations will tell me whether this is a good long-term fit. If it goes well, this becomes a standing monthly arrangement with a continuous stream of work.