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Python Data Developer Jobs (NOW HIRING)

Virtusa

Agentic AI developer

Tampa, FL

$114K - $154K/yr

The role requires deep expertise in Python, data engineering, and AI/GenAI (including LLMs), with a strong focus on delivering scalable, innovative solutions to complex business problems. The ...

Medinext Global LLC

Data Engineer

California City, CA · On-site

$140K - $168K/yr

Python * Data Engineering * Automation Scripting * Data Modeling * Dimensional Modeling * Normalization * Data Warehouse Design * OLTP vs. OLAP Architecture Understanding Experience Requirements:

ClifyX

Python Automation lead

Austin, TX · On-site

... in data engineering and Python ecosystems. • Lead the design and development of data processing pipelines leveraging Apache Spark and Scala. • Architect and implement backend services and APIs ...

Mindlance

Python Programmer

Washington, DC · On-site

The Enterprise Data Management (EDM) team is seeking a Python ETL Developer to work on sourcing data to their cloud platform. The candidate should have prior experience working in Python data stack ...

New

eSolutionsFirst, LLC

Sr. Python Developer

Mclean, VA · On-site

$51.50 - $71/hr

Python Full Stack Developer Mclean, VA Must Have Qualifications: Must have practical experience ... Python data processing technologies, e.g. Pandas, Numpy * Solid understanding on web applications ...

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Python Data Developer information

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How much do python data developer jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for python data developer in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

What is a Python data developer?

Python Data Developers are professionals who use the Python programming language to collect, process, and analyze data. They build and maintain data pipelines, write scripts for data manipulation, and work with databases to ensure data is accessible and usable for analytics and business insights. These developers often collaborate with data scientists, analysts, and other IT professionals to support data-driven decision-making within an organization.

What are the key skills and qualifications needed to thrive as a Python data developer, and why are they important?

To excel as a Python Data Developer, you need strong programming skills in Python, a solid understanding of data structures, algorithms, and experience with relational and NoSQL databases. Familiarity with data processing libraries (like Pandas, NumPy), ETL tools, and version control systems, as well as knowledge of cloud platforms (such as AWS or Azure), are typically required. Problem-solving ability, attention to detail, and effective communication are vital soft skills in this role. These skills enable efficient data pipeline development, ensure data quality, and facilitate collaboration within technical teams.

What are some common challenges faced by Python data developers when working with large datasets?

Python Data Developers often encounter challenges related to efficiently processing and managing large datasets, such as optimizing data pipelines for speed and memory usage. Handling data quality issues, integrating data from multiple sources, and ensuring scalability of their solutions are also frequent hurdles. Collaboration with data engineers, analysts, and stakeholders is crucial for understanding requirements and delivering robust results. Staying up to date with the latest libraries and tools, like Pandas, Dask, or PySpark, is also important to overcome these challenges and maintain high performance.

What is the difference between Python Data Developer vs Data Analyst?

AspectPython Data DeveloperData Analyst
Required SkillsPython, SQL, data modeling, ETL processesExcel, SQL, data visualization, basic statistics
CertificationsPython certifications, data engineering coursesData analysis certifications, Excel certifications
Work EnvironmentData engineering teams, software development projectsBusiness units, reporting teams
Industry UsageTech, finance, healthcare, where data pipelines are neededMarketing, finance, operations for insights and reporting

The Python Data Developer focuses on building data pipelines, integrating data sources, and developing scalable data solutions using Python. In contrast, Data Analysts primarily interpret data, create reports, and provide insights for decision-making. While both roles require SQL and data handling skills, Python Data Developers are more involved in data engineering tasks, whereas Data Analysts focus on data visualization and analysis.

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Python Data Developer jobs near you
Infographic showing various Python Data Developer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $121,932 per year, or $58.6 per hour.

AWS Python Data Engineer - Contract C2C jobs in Portland, OR

Tech Mirrors

Portland, OR • On-site

$80 - $130/hr

Other

Posted 3 days ago

New

Job description

Role- AWS Python Data Engineer

Location – Portland, OR (California/Oregon/Washington/Nevada)

Mandatory – Python, AWS, Cloud Native

Job Description

Seeking an experienced associate principal with expertise in Python and AWS Services to lead and development of serverless applications leveraging Python AWS Lambda and AWS S3. Architect and implement scalable modernization initiatives for cloud native solutions ensuring optimal performance and cost efficiency. Collaborate applications. Mentor and guide technical teams on Python development and AWS Cloud adoption strategies. Ensure SDKs and automation tools to streamline deployment and operational processes.

Responsibilities
  • Lead end-to-end delivery of cloud native solutions using Python and AWS Lambda.
  • Develop and maintain automation scripts for data ingestion validation and error handling using Python.
  • Establish CI/CD pipelines for Python applications, cloud architecture and deployment standards.
  • Monitor and troubleshoot AWS Lambda functions and S3 integrations.
  • Stay updated with emerging AWS.
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