Python appears on so many CVs that the word itself carries almost no signal. The useful question is which Python: a Django service handling web traffic, an Airflow estate moving data overnight, or a set of scripts holding an operations team together. Hiring managers filter on that distinction long before they look at years of experience.
A strong Python CV therefore commits early. The summary should make clear which of those worlds you work in, and the experience bullets should stay in it. Breadth can appear once, at the bottom, without diluting the top of the page.
This example is written for a backend-leaning Python developer with five years of experience across web services and asynchronous processing.
Backend Python developer with five years on Django and FastAPI services in logistics and fintech. Recent work covers a partner API serving 1.4m requests a day and a rewrite of the invoicing pipeline that cut its runtime by 85%. Comfortable owning schema design, background processing and the on-call rota for what I ship.
Professional Experience
Backend EngineerJanuary 2022 – Present
Tessellate Logistics · Bengaluru, India
•Own the partner-facing API in Django REST Framework: around 1.4m requests a day across nine integrators, with per-client rate limits and a published deprecation policy.
•Reworked the nightly invoicing job from a single 4-hour Celery task into 40 idempotent chunks with exponential backoff, taking runtime to 35 minutes and ending weekly manual reruns.
•Introduced mypy in strict mode across the billing package after a currency-rounding bug reached production; the same class of error has not recurred.
•Cut the pytest suite from 22 minutes to 6 by replacing database round-trips with factory_boy fixtures in around 300 tests.
•Handle second-line on-call for the service, and wrote the runbook covering the four incident types that account for most pages.
•Built the reconciliation service in FastAPI that matched settlement files from four acquirers against internal ledgers, replacing a spreadsheet process that took two people a day.
•Designed the retry and dead-letter handling for webhook delivery, which brought successful delivery from around 94% to 99.7%.
•Added Prometheus metrics and alerting for queue depth after a silent backlog went unnoticed for six hours.
Python · FastAPI · PostgreSQL · Redis · Docker
Projects
retryable
Maintainer
•A small Python package for declarative retry policies with jitter, budget limits and structured logging of every attempt.
•Around 30,000 downloads a month; used in production by the author and three external teams who have contributed fixes.
Python · asyncio · pytest
github.com/example-priyanair/retryable
Education
B.Tech Information TechnologyAugust 2016 – May 2020
Savitribai Phule Pune University · Pune, India
First Class with Distinction
Python Developer example on the Technical layout. All details are fictional and shown for demonstration only.
What recruiters expect
Before writing anything, it helps to know what the person reading is checking for. In this field that is usually a short, specific list:
A named framework and a real workload: Django, FastAPI or Flask, with request volumes or job counts attached.
Comfort with the parts of Python that bite in production - packaging, virtual environments, typing, the GIL and where it matters.
Testing discipline. pytest with fixtures and factories is close to a baseline expectation for backend roles.
Some database depth. ORM plus raw SQL, migration strategy, and awareness of N+1 queries.
Asynchronous or scheduled work: Celery, RQ, Airflow or asyncio, and how failures are retried.
Recommended CV structure
This is the running order the example uses. It is a starting point rather than a rule, but the order reflects what tends to be read first in this profession.
Profile — Three or four lines positioning you for the role.
Technical Skills — Grouped skills, for example "Languages" and "Tooling".
Professional Experience — Paid roles, in reverse chronological order.
Projects — Work you built, with outcomes and the stack used.
Education — Degrees, diplomas and school-leaving qualifications.
Certifications — Completed certifications with the issuing body.
Languages — Spoken languages with CEFR levels.
Sections worth adding
Open Source — Python has an unusually welcoming package ecosystem; a maintained library on PyPI is strong evidence.
Technical Writing — Conference talks and well-read blog posts substitute for open source if you have them.
Skills worth including
Grouped rather than listed in one block. Grouping makes a long list readable and shows that you can tell the difference between the things you use daily and the things you have touched.
Beyond the technical list: Code review, Writing runbooks, Debugging production incidents, Mentoring, Requirements analysis. These belong inside your experience bullets, demonstrated, rather than in a list of adjectives.
Example professional summary
Three or four lines, positioned for the role rather than describing your personality. Two versions you can adapt:
Backend Python developer with five years on Django and FastAPI services in logistics and fintech. Recent work covers a partner API serving 1.4m requests a day and a rewrite of the invoicing pipeline that cut its runtime by 85%. Comfortable owning schema design, background processing and the on-call pager for what I ship.
Python developer focused on asynchronous services and data integrity. Experience with Django, Celery and PostgreSQL in a team of eight, plus a maintained open-source package with roughly 30,000 monthly downloads.
Writing your experience
The difference between a CV that gets a call and one that does not is almost always in the bullet points. Each pair below shows a real rewrite of the kind of line that appears on most CVs in this field.
Weak
Built REST APIs with Django.
Stronger
Built and maintained the partner-facing API in Django REST Framework, serving around 1.4m requests a day across nine integrators, with rate limiting and a deprecation policy that let two clients migrate at their own pace.
Scale, audience and the operational thinking around versioning.
Weak
Used Celery for background tasks.
Stronger
Reworked the nightly invoicing job from a single 4-hour Celery task into 40 idempotent chunks with exponential backoff, taking the runtime to 35 minutes and ending the weekly manual reruns.
Shows understanding of idempotency and retries, which is what distinguishes production async work.
Weak
Improved test coverage.
Stronger
Introduced factory_boy fixtures and cut the pytest suite from 22 minutes to 6 by replacing database round-trips in 300 tests, which made the pre-merge check usable again.
Ties a technical change to the developer experience problem it solved.
Taken from the example
The sample CV for this profession is fully written. A few sections from it, so you can see the level of specificity that works:
Experience
Backend Engineer, Tessellate Logistics
Own the partner-facing API in Django REST Framework: around 1.4m requests a day across nine integrators, with per-client rate limits and a published deprecation policy.
Reworked the nightly invoicing job from a single 4-hour Celery task into 40 idempotent chunks with exponential backoff, taking runtime to 35 minutes and ending weekly manual reruns.
Introduced mypy in strict mode across the billing package after a currency-rounding bug reached production; the same class of error has not recurred.
Cut the pytest suite from 22 minutes to 6 by replacing database round-trips with factory_boy fixtures in around 300 tests.
Projects
retryable — A small Python package for declarative retry policies with jitter, budget limits and structured logging of every attempt.
Education
B.Tech Information Technology, Savitribai Phule Pune University — First Class with Distinction
Certifications and registration
Django Advanced Concepts — Test Driven
Common mistakes
Not saying which kind of Python developer you are
Web, data and automation are three different jobs. A CV that straddles all three reads as a generalist in a market that hires specialists.
Listing libraries instead of problems
"pandas, requests, BeautifulSoup" describes an afternoon, not a career. Attach each library to something you delivered.
Ignoring the data layer
Most Python backend interviews end up in the database. A CV with no query, index or migration detail leaves the strongest material unsaid.
Scripts presented as engineering
Automation is genuinely valuable, but describe it as automation: what it replaced, how often it runs, what happens when it fails.
ATS considerations
Applicant tracking systems behave differently by sector, and generic advice is often wrong for a given field. These points are specific to python developer applications:
Name the framework in the summary as well as the skills list. "Python developer" alone matches almost nothing specific.
Include "Django REST Framework" spelled out at least once; "DRF" on its own will not match.
Write "pytest" in lower case as the project does, but also include "unit testing" as a phrase for filters that search on the concept.
If the advert mentions type checking, include "type hints" and "mypy" explicitly rather than assuming "typed Python" covers it.
The Minimal ATS layout is built for this, and the ATS guide covers what parsers do to a file in more detail.
Questions about python developer CVs
Should I list Python 2 experience?
Only if you led a migration off it, in which case describe the migration. Listing it as a skill dates the CV without adding anything.
Is Django or FastAPI better to lead with?
Lead with whichever the advert names. If you have both, put both in the summary and let the experience bullets show where the depth is.
How do I present data work on a backend CV?
Keep it under the relevant job rather than creating a data section. If most of your work is pipelines, use the Data Analyst or Data Engineer framing instead - it will match more roles.
Do employers care about PyPI packages?
A maintained package with real users is one of the strongest signals available on a Python CV. A package with two downloads is not worth the line.