After this lesson, you will be able to: Translate Python skills into resume bullets, portfolio, and interview answers.
Python is hireable across many specialties: backend, data, ML, ops, scripting.
Python Backend Engineer (Django / FastAPI / Flask): $90-$170k. Data Engineer (Python + SQL + Spark): $110-$200k. ML Engineer / MLOps: $130-$240k. Data Analyst (Python + SQL): $70-$130k. Site Reliability Engineer (Python automation): $130-$220k. Search 'python engineer', 'data engineer', 'python developer' on LinkedIn.
Skills: Python 3.12+, type hints, pytest, asyncio, pyproject.toml, FastAPI / Django / Flask (pick one), pandas + NumPy, SQL, REST APIs, pyenv + venv. Projects: 'Published `yourtool` to PyPI; <download count> installs.' 'Built a FastAPI service with 50+ tests at 85% coverage; deployed to Render.' Certs: none canonical; pair with portfolio.
'Why is `def f(x, l=[]): l.append(x); return l` a bug?' (Mutable default.) 'How do you make 100 concurrent HTTP calls?' (asyncio.gather with httpx.) 'GIL, what is it, when does it matter?' 'Write a decorator that retries with backoff.' 'Compare async vs threads vs multiprocessing.'
Two in 30 days.
Ship pl-python-passion to PyPI + GitHub.
Write a blog: 'How I cut my Python script from 60s to 2s with asyncio'.
Contribute one PR to a major OSS Python project (FastAPI, requests, httpx, Click).
Pass 'Python Institute PCPP' or skip cert and double down on portfolio.
Record a 5-min Loom walking through your tool's design + tests.
Listing 'Python' without a public artefact. Python 2 mentioned anywhere in your portfolio. No type hints, reads as junior. Skipping async / data / testing in your answers, these are differentiators.
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