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Python Data Jobs (NOW HIRING)

TriosysIT Inc.

Python Developer

Columbus, OH · On-site

$47 - $64.75/hr

Python data processing technologies, e.g. Pandas, Numpy * Solid understanding on web applications, e.g. HTML, CSS, javascript * Solid understanding on DB and SQL

Compunnel

Python ETL Developer

Washington, DC · On-site

$57 - $78.50/hr

The role will involve sourcing data from internal and external sources, supporting existing ... Key Responsibilities • Use Python to perform ETL/ELT development and data processing activities ...

ClifyX

Azure Data Engineer (Python & AI/ML)

Cincinnati, OH · On-site

$111K - $134K/yr

ClifyX is a company specializing in data solutions, and they are seeking an Azure Data Engineer with expertise in Python and AI/ML. The role focuses on leveraging Microsoft Azure data services to ...

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How much do python data jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for python data 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 professional?

A Python Data professional is someone who uses the Python programming language to analyze, process, and interpret data. They work with large datasets, perform data cleaning and transformation, and apply statistical or machine learning techniques to extract insights. These professionals often work in roles such as data analyst, data scientist, or data engineer, and use Python libraries like Pandas, NumPy, and scikit-learn to accomplish their tasks.

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

To thrive as a Python Data professional, you need strong programming skills in Python, a solid understanding of data structures, algorithms, and experience with data analysis or data science, typically supported by a relevant degree. Familiarity with technical tools such as pandas, NumPy, SQL, Jupyter Notebooks, and often cloud platforms or machine learning frameworks is important, and certifications like Microsoft or Google Data certifications can be advantageous. Strong analytical thinking, attention to detail, and effective communication help you extract insights from data and collaborate with stakeholders. These skills and qualities are essential to efficiently process, analyze, and interpret data, driving informed business decisions.

What are some common challenges faced by Python Data professionals when working with large datasets?

Python Data professionals often encounter challenges such as optimizing code to handle large volumes of data efficiently and managing memory usage to prevent slowdowns or crashes. Working with big datasets may require leveraging tools like pandas, NumPy, or Dask, and sometimes integrating with distributed computing systems such as Apache Spark. Additionally, ensuring data quality and managing data pipelines for consistent and accurate results can be demanding. Collaborating closely with data engineers, analysts, and other stakeholders is common to ensure smooth data flow and analysis.

What is the difference between Python Data vs Data Analyst?

AspectPython DataData Analyst
Required SkillsPython programming, data manipulation, scriptingExcel, SQL, data visualization
CertificationsPython certifications, data science coursesData analysis certifications, Excel certifications
Work EnvironmentData science teams, programming-heavy rolesBusiness intelligence, reporting teams
Industry UsageTech, finance, healthcareRetail, marketing, finance

Python Data roles focus on programming, data manipulation, and building data pipelines using Python, while Data Analysts primarily analyze data using tools like Excel and SQL to generate reports and insights. Both roles often collaborate but differ in technical depth and tools used.

Are Python coders in demand?

Python developers are in high demand across various industries due to the language's versatility in data analysis, web development, and automation. Employers seek skills in frameworks like Django and data tools such as Pandas, making Python a valuable programming language for job seekers. The demand is expected to grow as data-driven decision-making and automation increase in the workplace.

How much do Python data scientists make?

Python data scientists typically earn a median salary ranging from $90,000 to $130,000 annually, depending on experience, location, and industry. Advanced skills in machine learning, data analysis, and proficiency with tools like Pandas and TensorFlow can lead to higher compensation.

Is Python Data still in demand in 2026?

Python data roles remain in high demand in 2026 due to the language's widespread use in data analysis, machine learning, and automation. Skills in libraries like Pandas, NumPy, and frameworks such as TensorFlow enhance job prospects, and proficiency in data management tools is often required.
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Python Data jobs near you
Infographic showing various Python Data 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.

Python Developer

TriosysIT Inc.

Columbus, OH • On-site

$47 - $64.75/hr

Other

Re-posted 15 days ago

Job description

Work Arrangement : Onsite

Location : Wilmington, DE / Columbus, Ohio

Key Responsibilities:

  • Design, develop and support systems within the financial modeling and research area.
  • Design and develop new code and review existing code changes to ensure standard technology development practices are met.
  • Assist in the operational execution of software solutions to assist with the monitoring and control of market and credit risks.
  • Assist with application development and modifying and/or maintaining applications; Demonstrate knowledge of development tools and languages.
  • Assist other areas of financial research and engineering when defining requirements for systems applications.

Key Requirements and Technology Experience:

  • Must have skills: - Python, JavaScript, SQL, quantitative finance
  • Quantitative finance
  • Python
  • Python web technologies, e.g. Flask, Dash
  • Python data processing technologies, e.g. Pandas, Numpy
  • Solid understanding on web applications, e.g. HTML, CSS, javascript
  • Solid understanding on DB and SQL

Apply