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Fastapi Python Jobs in Draper, UT (NOW HIRING)

Integration Engineer

Midvale, UT · On-site +1

$50 - $65/hr

Experience with FastAPI or similar modern Python web frameworks. * Strong understanding of asynchronous programming concepts and Python asyncio. * Experience working with PostgreSQL databases.

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Fastapi Python information

See Draper, UT salary details

$12

$54

$80

How much do fastapi python jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for fastapi python in Draper, UT is $54.80, according to ZipRecruiter salary data. Most workers in this role earn between $45.19 and $62.26 per hour, depending on experience, location, and employer.

What is the difference between Fastapi Python vs Django Developer?

AspectFastapi PythonDjango Developer
Primary FocusBuilding high-performance APIsDeveloping full-stack web applications
FrameworkFastapiDjango
Work EnvironmentBackend API services, microservicesWeb applications, content management systems
Required SkillsPython, asynchronous programming, REST APIsPython, Django framework, HTML/CSS, databases

Fastapi Python developers specialize in creating fast, scalable APIs using the Fastapi framework, often for microservices and backend systems. Django developers focus on building comprehensive web applications with integrated features. Both roles require Python, but Fastapi emphasizes performance and asynchronous programming, while Django offers a full-stack solution.

What cities near Draper, UT are hiring for Fastapi Python jobs? Cities near Draper, UT with the most Fastapi Python job openings:
Python Data Engineer / API Developer

Python Data Engineer / API Developer

Inficare Technologies

Salt Lake City, UT • On-site

$48.50 - $67/hr

Full-time

Posted 6 days ago


Job description

Role : Python Data Engineer / API Developer
Location: Salt Lake City Its day 1 onsite
Duration: Long term
Key: Python, PySpark, GCP, API development
Role Overview
We are seeking a highly skilled Python Data Engineer / API Developer with strong hands-on experience in PySpark, cloud-based data engineering on GCP, and API development. The ideal candidate should have expertise in building scalable data pipelines, working with distributed clusters, and developing secure APIs for enterprise-grade applications.
Key Responsibilities
  • Design, develop, and maintain scalable data pipelines for batch and/or real-time processing.
  • Build and optimize PySpark applications running on distributed clusters.
  • Develop secure and scalable Python-based APIs.
  • Work with cloud-native GCP services including BigQuery, Composer, DAGs, and Cloud Storage Buckets.
  • Implement data quality checks, validations, and monitoring frameworks within pipelines.
  • Collaborate with cross-functional teams including data analysts, BI teams, and platform engineers.
  • Ensure performance optimization, reliability, and security best practices across solutions.

Required Skills & Qualifications
  • Strong hands-on experience with PySpark and distributed cluster computing.
  • Proven experience in building Python APIs with a focus on security and scalability.
  • Strong knowledge of API frameworks such as FastAPI or Flask.
  • Hands-on experience with Google Cloud Platform (GCP) services:
    • BigQuery
    • Composer
    • DAG orchestration
    • Cloud Storage Buckets
  • Experience in building robust batch and/or real-time data pipelines.
  • Strong understanding of data quality frameworks and practices.

Preferred Skills
  • Experience with BI and reporting tools such as:
    • Power BI
    • MicroStrategy
  • Familiarity with CI/CD pipelines and DevOps practices is an added advantage.
  • Exposure to data governance and monitoring tools is a plus.