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APIs with product empathy
Contract-first services, clean auth, and documentation that keep stakeholders and partners aligned.
Hire Python developers for APIs and data products.
Python experts who deliver secure services, data pipelines, and integrations with confidence.
Deeptal Python engineers ship web services, ETL, and automation with strong testing, observability, and rollback practices.
Hire a top Python developer nowNo-risk trial. Pay only if satisfied.
Clients rate Deeptal Python teams 4.9 / 5.0 on average.
Pulse surveys after onboarding and milestone readouts.Compensation snapshot
Bench-readyAnnual bands across key markets to plan budgets confidently.
US & Canada
$112k – $168k
Glassdoor Oct 2025, total comp
United Kingdom
£55k – £82k
Glassdoor Oct 2025, total comp
Germany
€58k – €80k
Glassdoor Oct 2025, total comp
The Balkans
€32k – €58k
Glassdoor Oct 2025, total comp
Avg. seniority
8.8 yrs
Launch readiness
10-14 days
From brief to onboarding
API + data coverage
Django · FastAPI · ETL
Quality gates from sprint 1
Trusted by product and engineering teams
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Delivery highlights
What you get with Deeptal
Senior talent, clear rituals, and proactive communication from week one.
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Data workflows you can trust
ETL and streaming pipelines with testing, observability, and clear ownership so analytics stay reliable.
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Automation that sticks
CI/CD, task orchestration, and platform hooks to eliminate toil without breaking delivery cadence.
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Security-minded delivery
Dependency hygiene, secrets management, and privacy reviews included from the first sprint.
Coverage map
Where this team drives outcomes
Where Python teams excel
Common outcomes we deliver for product, platform, and data leaders.
- Building and scaling APIs for web/mobile products with strict SLAs.
- Standing up ETL/ELT pipelines, streaming jobs, and data quality guardrails.
- Automating internal workflows with clear auditability and documentation.
- Modernizing legacy Python services with tests, typing, and observability.
Delivery with confidence
Habits that keep services and data pipelines reliable.
- CI/CD with contract tests, linting, type checks, and canary/rollback strategies.
- Observability coverage across APIs, workers, and data flows.
- Security checks for dependencies, secrets, and access control.
- Runbooks and on-call routines sized to your team and budget.
Specialties
Specialist coverage by pod
Web services
Django/FastAPI/FlaskREST/GraphQL contractsAuth, caching, queuingPerformance + profiling
Data & ML plumbing
ETL/ELT pipelinesAirflow/Prefect orchestrationData quality + lineageModel serving foundations
Operations
CI/CD + automationObservability + alertingInfrastructure as codeRunbooks + handover
Sample talent
Meet ready-to-start specialists
Profiles curated for your stack, time zones, and delivery rituals.
Camila T.
Senior Python Engineer
Lisbon | GMT
FastAPI, PostgreSQL, Redis, Kubernetes
Built contract-tested APIs and background workers for a logistics platform, adding tracing and rate limiting to keep SLAs steady.
Omar A.
Data Platform Engineer
Chicago | CST
Airflow, dbt, Snowflake, Python
Designed ELT pipelines with lineage and quality checks, pairing closely with analytics teams and tightening CI for SQL/Python assets.
Meera L.
Python Tech Lead
Singapore | GMT+8
Django, Celery, GraphQL, AWS
Led a marketplace rebuild with GraphQL, task orchestration, and observability that reduced incident time-to-detect by 35%.
Hiring playbook
How to hire Python developers
Python engineers should cover APIs, data workflows, and reliability practices without sacrificing delivery speed.
Anchor on API + data outcomes
- Share the user journeys, integrations, and data freshness needs that matter most.
- Ask candidates to walk through how they balanced API design, data models, and delivery speed.
Check framework versatility
- Discuss experience with Django/FastAPI/Flask and when they choose each.
- Probe knowledge of background jobs, caching, and schema evolution patterns.
Validate reliability and observability
- Review how they structure tests, monitoring, and alerting across services and pipelines.
- Look for runbooks, incident experience, and a bias toward rollback safety.
Assess collaboration with data and product
- Great Python engineers pair with analysts, ML teams, and PMs without friction.
- Listen for habits around documentation, data contracts, and experimentation.
How it works
Engage in three clear steps
1
Talk to a delivery lead
Clarify roadmap, integrations, and data needs so we calibrate the slate correctly.
2
Meet hand-selected talent
Review a shortlist of Python seniors with the frameworks, domains, and time zones you need.
Most clients see candidates within 48 hours.
3
Start with a no-risk sprint
Kick off a trial with clear scope and success criteria. Swap or scale quickly if the fit is not perfect.
Pay only if satisfied after the initial milestone.
Exceptional talent
How we source the top Python developers
We continuously vet Python specialists for API design, data workflows, and delivery habits.
Every engineer is screened for communication, documentation, and observability skills.
Thousands apply each month. Only top talent are accepted.
Step 1
Language & collaboration evaluation
Communication, requirement-gathering, and documentation signals to ensure smooth team fit.
Step 2
API + data deep dive
Technical screening on Python frameworks, data modeling, orchestration, and reliability practices.
Step 3
Live problem solving
Optional: Your team can join
Hands-on exercises covering API trade-offs, data quality, and debugging under time constraints.
Step 4
Test project
Optional: You can provide your own brief
A scoped project to validate delivery cadence, observability, and documentation quality.
Step 5
Continued excellence
Scorecards, engagement reviews, and playbook contributions to stay on the Deeptal bench.
Capabilities
Capabilities of Python developers
Our Python teams excel in services, data pipelines, and automation with security and observability built in.
API and service development
Django, FastAPI, and Flask builds with clean contracts, auth, caching, and background jobs.
Data pipelines and orchestration
ETL/ELT design with Airflow, Prefect, or Dagster plus testing, lineage, and quality checks.
Streaming and event-driven flows
Kafka- or Redis-backed messaging patterns with retry logic and idempotency.
Automation and DevOps
CI/CD, containerization, and infrastructure-as-code to keep deployments consistent.
Performance and reliability
Profiling, async patterns, and observability to keep latency predictable.
Security and compliance
Secrets management, dependency hygiene, and auditing aligned with your governance needs.
Trusted by product and data leaders
Find the right Python talent for every project
From API specialists to data-focused leads, Deeptal teams match your Python stack and time zones.
Django/FastAPI engineers
Builders of secure, well-documented services with background jobs and caching tuned.
Data pipeline engineers
Experts in ETL/ELT, orchestration, data quality, and analytics enablement.
Automation-focused ICs
Engineers who eliminate toil with CI/CD, scripting, and internal tooling.
Python tech leads
Leads who guide architecture, observability, and collaboration across product and data teams.
FAQs
How much does it cost to hire a Python developer?▾
Glassdoor data from October 2025 shows median total compensation around $138,000 in the US, £79,000 in the UK, and €80,000 in Germany. Costs vary by seniority, region, and engagement model; we calibrate to your budget before kickoff.
How quickly can I meet vetted Python talent?▾
Most clients see calibrated shortlists within 48 hours and can start a trial within 10–14 days once the brief is clear.
Do you handle both APIs and data pipelines in Python?▾
Yes. We staff Python engineers for web services (Django/FastAPI/Flask) and for ETL/streaming with orchestration, testing, and observability.
How do you vet Python talent for performance and reliability?▾
We run Python-specific screens, review past performance tuning work, and use test projects. References confirm they have delivered reliable services in production.
Can you help modernize legacy Python codebases?▾
Yes. We add tests, align dependencies, improve typing where useful, and phase refactors with feature flags to avoid regressions.
Explore services
Explore related Deeptal services
Looking for end-to-end delivery? Browse Deeptal programs across technology, marketing, and consulting.
Hiring guide
How to hire Python developers
Python powers APIs, automation, and data products—often within the same team.
Use this guide to spot engineers who ship calmly across services and pipelines.
Are Python developers in demand?
Yes. Python remains a top language for product delivery, automation, and data work.
Engineers who balance API craft, data fluency, and reliability habits are scarce.
What distinguishes great Python engineers?
They design clear contracts, keep pipelines observable, and automate quality gates.
They can shift between product features, data workflows, and platform concerns without losing velocity.
Core layers to cover
Services: frameworks, auth, background jobs, caching, and testing discipline.
Data: modeling, orchestration, quality checks, and lineage.
Operations: CI/CD, observability, security, and rollback strategies.
How to run the process
Define API and data outcomes plus reliability targets upfront.
Review code samples and incident retros; run a scoped project to watch collaboration.
Ensure candidates can explain trade-offs and document decisions clearly.
When to pick specialists vs. generalists
Choose specialists for heavy data/ML workloads or complex API programs.
Choose generalists for blended product squads that need steady cross-surface delivery.
Median total compensation (Glassdoor, Oct 2025, USD equivalent)
USA
$138,000
Canada
$104,000
United Kingdom
$79,000
Germany
$80,000
Romania
$46,000
Ukraine
$50,000
India
$18,000
Australia
$109,000
Top Python engineers are in high demand.
Launch API and data workstreams quickly with seniors who keep quality and observability in view.